Thiruvananthapuram, the capital city of Kerala, is renowned for its blend of rich heritage, stunning landscapes, and vibrant culture. Whether you’re exploring its serene beaches, historic temples, or lush greenery, having a reliable mode of transportation can make your journey hassle-free. Motoshare’s newly launched bike and car rental services in Thiruvananthapuram ensure you have the freedom to explore the city at your own pace. Here’s everything you need to know about Motoshare and your next adventure in Thiruvananthapuram.

Motoshare Services: Seamless Rentals at Your Fingertips

Motoshare is a user-friendly platform that connects renters with vehicle owners in Thiruvananthapuram. With just a few clicks, you can book a bike or car tailored to your travel needs, ensuring convenience and cost-effectiveness.

• Car Rentals in Thiruvananthapuram: Explore car rental options for comfortable and spacious rides.
• Bike Rentals in Thiruvananthapuram: Discover bike rental options for quick and adventurous commutes.

Why Choose Motoshare?

• Convenience: An intuitive platform that simplifies the booking process.
• Affordability: Competitive pricing by renting directly from vehicle owners.
• Variety: A wide range of vehicles to suit different travel preferences.
• Safety: Trusted platform with secure transactions and well-maintained vehicles.
• Flexibility: Options for short-term and long-term rentals to match your itinerary.

Top 10 Places to Visit in Thiruvananthapuram

Once you’ve secured your rental vehicle, explore these must-visit attractions in Thiruvananthapuram:

1. Padmanabhaswamy Temple
   • Best Time to Visit: Early morning for darshan.
   • Why Go: A historic temple renowned for its architectural brilliance and spiritual significance.
2. Kovalam Beach
   • Best Time to Visit: Evening for mesmerizing sunsets.
   • Why Go: A world-famous beach offering stunning views and water sports activities.
3. Napier Museum
   • Best Time to Visit: Afternoon for a cultural experience.
   • Why Go: Explore artifacts, art, and historical exhibits.
4. Shanghumukham Beach
   • Best Time to Visit: Evening for relaxation.
   • Why Go: A serene beach with a large sculpture of a mermaid and peaceful surroundings.
5. Poovar Island
   • Best Time to Visit: Winter months for pleasant weather.
   • Why Go: Enjoy a boat ride through tranquil backwaters and golden beaches.
6. Neyyar Wildlife Sanctuary
   • Best Time to Visit: Morning for wildlife sightings.
   • Why Go: A haven for nature lovers with trekking and a lion safari.
7. Agasthyakoodam
   • Best Time to Visit: Winter for trekking.
   • Why Go: A popular trekker’s destination and a biodiversity hotspot.
8. Vizhinjam Lighthouse
   • Best Time to Visit: Sunset for panoramic views.
   • Why Go: A historic lighthouse offering stunning vistas of the Arabian Sea.
9. Veli Tourist Village
   • Best Time to Visit: Morning for boat rides.
   • Why Go: A scenic spot with lagoons, gardens, and adventure activities.
10. Kanakakunnu Palace
    • Best Time to Visit: Evening for events and exhibitions.
    • Why Go: A cultural hub and architectural marvel set amidst lush greenery.

Bonus Recommendations

For unique experiences, consider:

• Kuthiramalika Palace Museum: A historic palace showcasing traditional Kerala architecture.
• Akkulam Lake: A serene spot for picnics and family outings.
• Varkala Beach: A short drive away, perfect for cliffside views and spiritual vibes.

Advantages of Renting with Motoshare

1. Wide Selection of Vehicles: From bikes to cars, find the perfect ride for your trip.
2. Affordable Prices: Direct rentals from owners ensure budget-friendly options.
3. User-Friendly Platform: Effortless browsing and quick bookings.
4. Flexible Rentals: Adjust rental durations to match your plans.
5. Local Expertise: Gain travel tips and insights from vehicle owners.
6. Secure Payments: Trusted and reliable payment processes.

How to Rent with Motoshare

1. Sign Up: Create an account on Motoshare’s website.
2. Search Vehicles: Browse through the available bikes and cars in Thiruvananthapuram.
3. Book Your Ride: Select your preferred vehicle, confirm dates, and make your booking.
4. Pick Up & Explore: Coordinate with the owner and begin your Thiruvananthapuram adventure.

Plan Your Thiruvananthapuram Journey Today!

With Motoshare, exploring Thiruvananthapuram has never been easier. Whether you’re visiting its iconic landmarks, serene beaches, or vibrant markets, our bike and car rentals provide the perfect travel solution. Start your journey now by visiting:

• Car Rentals in Thiruvananthapuram
• Bike Rentals in Thiruvananthapuram

Experience Thiruvananthapuram with the freedom and flexibility of Motoshare. Happy exploring!

The post A Traveler’s Guide to Motoshare Rentals in Thiruvananthapuram appeared first on Artificial Intelligence.

Rajkot, a city steeped in history and culture, is one of Gujarat’s most vibrant destinations. Whether you’re here to explore its rich heritage, indulge in local cuisine, or experience the city’s modern charm, Motoshare’s bike and car rental services make getting around effortless.

With Motoshare, you can rent vehicles directly from local owners, ensuring affordability and convenience. In just a few clicks on Motoshare’s platform, you can book the perfect ride for your journey in Rajkot.

An Overview of Motoshare Services

Motoshare simplifies vehicle rentals by connecting renters with vehicle owners. Whether you need a bike for quick errands or a car for a family outing, Motoshare ensures a smooth and hassle-free experience.

Why Choose Motoshare?

• Variety of Options: Choose from a wide range of bikes and cars to suit your preferences.
• Affordable Prices: Enjoy competitive rates with no hidden charges.
• Convenient Booking: A seamless online process lets you book your ride in minutes.
• Flexible Rentals: Rent for hours, days, or weeks, based on your needs.
• Trusted Service: Well-maintained vehicles ensure a reliable experience.

Start your journey today:

• Car Rentals in Rajkot: Click here
• Bike Rentals in Rajkot: Click here

Top 10 Places to Visit in Rajkot with Your Motoshare Rental

With its rich heritage and cultural vibrancy, Rajkot is a city worth exploring. Here’s a list of must-visit places to explore with your Motoshare bike or car:

1. Kaba Gandhi No Delo

• Why Visit? A historical landmark that served as Mahatma Gandhi’s residence during his early years.
• Best Time: Morning for a peaceful tour.
• Highlight: A museum showcasing Gandhi’s life and teachings.

2. Rotary Dolls Museum

• Why Visit? A unique collection of over 1,500 dolls from around the world.
• Best Time: Afternoon for a leisurely visit.
• Highlight: Learn about global cultures through the intricately designed dolls.

3. Watson Museum

• Why Visit? A treasure trove of Rajkot’s colonial and cultural history.
• Best Time: Morning for guided tours.
• Highlight: Artifacts, sculptures, and exhibits that narrate the city’s past.

4. Jubilee Garden

• Why Visit? A serene green space in the heart of the city, ideal for picnics and relaxation.
• Best Time: Evening for pleasant weather.
• Highlight: The garden’s iconic landmarks, such as the Connaught Hall and Alfred High School.

5. Race Course Ground

• Why Visit? A hub of activities with sports complexes, parks, and food stalls.
• Best Time: Early morning for fitness activities or evening for a lively atmosphere.
• Tip: Great for families with kids.

6. Aji Dam

• Why Visit? A scenic dam perfect for a day of tranquility and picnics.
• Best Time: Winter for pleasant weather.
• Highlight: Aji Dam Garden with lush greenery and fountains.

7. Ishwariya Park

• Why Visit? A popular recreational spot for families and couples.
• Best Time: Sunset for beautiful views.
• Highlight: Boating and walking trails within the park.

8. Khambhalida Caves

• Why Visit? Ancient Buddhist caves with intricate carvings and a serene atmosphere.
• Best Time: Early morning to avoid crowds.
• Tip: A must-visit for history enthusiasts and photographers.

9. Fun World Amusement Park

• Why Visit? A fun-filled destination with rides and activities for all age groups.
• Best Time: Evening for cool weather and vibrant lights.
• Highlight: A perfect family outing spot.

10. Lal Pari Lake

• Why Visit? A picturesque lake ideal for birdwatching and nature photography.
• Best Time: Winter months when migratory birds visit.
• Highlight: A serene retreat from the hustle of city life.

Advantages of Renting with Motoshare in Rajkot

1. Flexibility: Travel at your own pace and explore every corner of the city.
2. Convenient Rentals: Choose a bike for quick trips or a car for family outings.
3. Budget-Friendly Options: Affordable prices make it accessible for everyone.
4. Easy Online Booking: Spend less time booking and more time exploring.
5. Trusted Vehicles: Well-maintained bikes and cars for a smooth ride.

Start Your Rajkot Adventure with Motoshare Today!

Rajkot is a city full of stories waiting to be discovered. Whether you’re visiting for a day or staying longer, Motoshare’s bike and car rentals provide the perfect travel solution. Enjoy the freedom to create your own itinerary and explore the city at your own pace.

Ready to Begin?

• Rent your bike in Rajkot
• Rent your car in Rajkot

Visit Motoshare today to book your ride and experience Rajkot like never before.

The post A Guide to Renting Vehicles in Rajkot with Motoshare appeared first on Artificial Intelligence.

Ahmedabad, the vibrant heart of Gujarat, is a city that beautifully blends centuries-old traditions with modern urban life. Whether you’re a traveler soaking in the rich culture or a local looking for a convenient way to explore, Motoshare’s bike and car rental services are here to redefine your experience. With just a few clicks on Motoshare’s platform, you can rent a vehicle directly from owners and set out to discover Ahmedabad’s charm at your own pace.

An Overview of Motoshare’s Services

Motoshare has revolutionized bike and car rentals in Ahmedabad by offering a seamless and efficient platform for travelers and locals alike. Whether you need a zippy bike to navigate the city streets or a comfortable car for a family outing, Motoshare connects you to a range of vehicles, ready for your journey.

Here’s why Motoshare is the perfect choice:

• Wide Variety of Vehicles: From economical options to premium models, Motoshare has it all.
• Direct Owner Rentals: Skip intermediaries and connect directly with vehicle owners for better deals.
• Affordable Prices: Enjoy competitive rental rates with no hidden charges.
• Flexible Rental Durations: Choose from hourly, daily, or weekly rental plans.
• Simple Online Process: Book your vehicle in minutes through the Motoshare platform.

Access rental services now:

• Car Rentals in Ahmedabad: Click here
• Bike Rentals in Ahmedabad: Click here

Advantages of Choosing Motoshare in Ahmedabad

1. Convenience at Your Fingertips: No lengthy paperwork or complicated processes. Book your ride online with ease.
2. Direct Owner Interaction: Transparency and trust are at the core of Motoshare’s operations.
3. Cost-Effective Options: Save money by renting directly from vehicle owners.
4. Customizable Experiences: Choose the perfect ride for your specific travel needs.
5. Support for Local Economy: Renting from local owners helps build community connections.

Top 10 Places to Visit in Ahmedabad with Your Motoshare Rental

Whether you’re driving a car or cruising on a bike, Ahmedabad is brimming with attractions that promise an unforgettable experience. Here’s a curated list of must-visit places to explore with your Motoshare rental:

1. Sabarmati Ashram

• Why Visit? A serene retreat with profound historical significance, it’s where Mahatma Gandhi’s vision of India took shape.
• Best Time: Morning hours for a peaceful experience.
• Must-See: Gandhi’s living quarters, the museum, and the Sabarmati Riverfront.

2. Kankaria Lake

• Why Visit? Perfect for family outings with activities like boating, a zoo, and a toy train.
• Best Time: Evenings to enjoy the cool breeze and light shows.
• Tip: Don’t miss the balloon safari for stunning aerial views.

3. Adalaj Stepwell

• Why Visit? A mesmerizing example of Indo-Islamic architecture, showcasing intricate carvings.
• Best Time: Early morning to avoid crowds.
• Fun Fact: It was a social hub in ancient times for travelers and locals alike.

4. Sidi Saiyyed Mosque

• Why Visit? Known for its stunning stone lattice work, particularly the “Tree of Life” design.
• Best Time: Midday when sunlight accentuates the carvings.
• Tip: Ideal for photography enthusiasts.

5. Manek Chowk

• Why Visit? A bustling food market that transforms into a street food haven by night.
• Best Time: Post 8 PM for authentic local dishes like khaman and jalebi.
• Pro Tip: Arrive hungry!

6. Science City

• Why Visit? A fun and educational destination for families with its interactive exhibits, planetarium, and IMAX theatre.
• Best Time: Weekdays to avoid crowds.
• Kid’s Favorite: The Robotics Gallery and Virtual Reality Zones.

7. Jhulta Minara (Shaking Minarets)

• Why Visit? A unique architectural phenomenon where one minaret vibrates when the other is shaken.
• Best Time: Early morning for a quieter exploration.
• Tip: Ask a local guide to demonstrate this fascinating feature.

8. Calico Museum of Textiles

• Why Visit? A globally renowned museum celebrating Ahmedabad’s textile heritage.
• Best Time: Morning slots (requires prior booking).
• Highlight: Intricate 17th-century textiles on display.

9. Law Garden Night Market

• Why Visit? A shopper’s paradise offering vibrant traditional Gujarati attire and handicrafts.
• Best Time: Evening.
• Pro Tip: Bargain like a local for the best deals.

10. Akshardham Temple

• Why Visit? A spiritual haven combined with stunning architecture and enlightening exhibitions.
• Best Time: Late afternoon for the light and water show.
• Must-Experience: The Sahaj Anand Water Show, a visual treat for all ages.

Plan Your Adventure with Motoshare Today!

Ahmedabad is a city that deserves to be explored at your own pace, and Motoshare makes it possible. With its hassle-free bike and car rental services, you can design your travel itinerary without the constraints of public transport or tour schedules.

Your Journey Begins Here:

• Explore Motoshare’s bike rental options in Ahmedabad
• Discover flexible car rental solutions in Ahmedabad

Book your ride today at www.motoshare.in and experience the freedom of personalized travel in Ahmedabad!

The post Your Guide to Renting Bikes and Cars in Ahmedabad with Motoshare appeared first on Artificial Intelligence.

What is Azure?

Azure is launched by Microsoft in February 2010.

It is a cloud computing platform including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) and also these can be used for services such as analytics, virtual computing, storage, networking, etc.

The Azure cloud platform has more than 200 products and cloud services designed to help the users and to solve today’s challenges and create the future.

What is the use of Azure?

There are 10 uses of Azures –

• Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) capabilities:
• Security Offerings:
• Scalability and Ductility:
• Unmatched Hybrid Capabilities:
• Integrated Environment with Other Microsoft Tools:
• Analytics and Intelligence capabilities:
• Easy learning curve:
• Cost Efficient Platform:
• Interoperability:
• Identity & Access Management (IAM):

Compare Google Cloud Certification Vs Azure Certification Vs AWS

Amazon Web Services (AWS) –

AWS is the most widely used cloud platform, having a very vast experience with an expansive range of services tailored for different use cases. AWS is currently at the top, holding the world’s largest public cloud market share. It has been introduced in 2006 and was the first to offer infrastructure services through the Internet.

AWS incorporates many different cloud computing products and services comprising compute, storage, analytics, databases, networking, mobile, developer tools, management tools, and IoT.

Key Features of AWS

• Reliable, scalable, and low-cost infrastructure platform
• Over 200 fully-featured services
• A flexible and secure cloud computing environment
• 81 availability zones in 25 geographic regions across the world

Microsoft Azure–

Azure is the second-largest Cloud Service Provider after AWS. Microsoft Azure is Microsoft’s public cloud computing platform that was introduced in October 2008 and became available in public in February 2010. It is the biggest competitor of AWS. The platform provides a broad range of products and cloud services to allow businesses to find today’s challenges and create the future. Azure’s product portfolio comprises compute, AI & Machine Learning, analytics, databases, DevOps, IoT, networking, storage, web, and security.

Key Features of Azure

• More than 200 products and cloud services
• 90+ compliance offerings
• 95 percent of the Fortune 500 companies rely on Azure
• Datacentres in 60+ global regions

Google Cloud Platform–

GCP is new to cloud computing offered by Google. Many leading companies over industries keep faith on Google Cloud to solve their business problems. Some of its popular cloud services comprise computing, data analytics, data storage, networking, IoT, and machine learning.

Between all three cloud platforms, GCP provides the low-cost pricing model and has flexible cost-control, enable you to try the different services and features.

Key Features of GCP

• Open source, multi-cloud, and hybrid cloud
• Over 100 products
• A global network spanning across 200+ countries & territories, 85 zones
• Trust and security

Certification

The certification confirms your basic knowledge of cloud services and how those services are offered with Azure. Candidates should be competent to demonstrate a fundamental knowledge of cloud concepts, alongside with Azure services, workloads, security, privacy, pricing, and support.

A Microsoft azure certification allows you to chase a wide range of career options. You can become a cloud architect, a developer or solution architect. Additionally, the certification allows you to work in different industries at different locations.

List of Azure Certification

• Microsoft Certified: Azure – Fundamentals Exam AZ-900
• Microsoft Certified: Azure AI – Fundamentals Exam AI-900
• Microsoft Certified: Azure Data – Fundamentals Exam DP-900
• Microsoft Certified: Azure Administrator – Associate Exam AZ-104
• Microsoft Certified: Azure Developer – Associate Exam AZ-204
• Microsoft Certified: Azure Security Engineer – Associate Exam AZ-500
• Microsoft Certified: Azure AI Engineer – Associate Exam AI-100
• Microsoft Certified: Azure Data Scientist – Associate Exam DP-100
• Microsoft Certified: Azure Data Engineer – Associate Exams DP-200 and DP-201
• Microsoft Certified: Azure Database Administrator – Associate Exam DP-300
• Microsoft Certified Solutions Architect – Expert Exams AZ-303 and AZ-304
• Microsoft Certified: Azure DevOps Engineer – Expert Exam AZ-400

Azure Certification Path

Fundamentals-Level Certifications

• Microsoft Certified: Azure Fundamentals AZ-900
• Microsoft Certified: Azure Data Fundamentals DP-900
• Microsoft Certified: Azure AI Fundamentals AI-900
• Microsoft Security, Compliance, and Identity Fundamentals Azur SC-900

Associate-Level Certifications

• Microsoft Certified: Azure Administrator Associate AZ-104
• Microsoft Certified: Azure Developer Associate AZ-204
• Microsoft Certified: Azure Database Administrator Associate DP-300
• Microsoft Certified: Azure Security Engineer Associate AZ-500
• Microsoft Certified: Azure Data Engineer Associate DP-203
• Microsoft Certified: Azure AI Engineer Associate AI-102
• Microsoft Certified: Azure Stack Hub Operator Associate AZ-600

Expert-Level Certifications

• Microsoft Certified: Azure Solutions Architect Expert AZ-303
• Microsoft Certified: DevOps Engineer Expert AZ-400

Specialty Certifications

• Microsoft Certified: Azure IoT Developer Specialty AZ-220
• Microsoft Certified: Azure for SAP Workloads Specialty AZ-120

Azure Certification Cost

• Azure Fundamentals AZ-900 – ( $99 USD* )
• Azure Data Fundamentals DP-900 – ( $99 USD* )
• Azure AI Fundamentals AI-900 – ( $99 USD* )
• Microsoft Security, Compliance, and Identity Fundamentals Azur SC-900 – ( $99 USD* )
• Azure Administrator Associate AZ-104 – ( $165 USD* )
• Azure Developer Associate AZ-204 – ( $165 USD* )
• Azure Database Administrator Associate DP-300 – ( $165 USD* )
• Azure Security Engineer Associate AZ-500 – ( USD 165.00* )
• Azure Data Engineer Associate DP-203 – ( USD 165* )
• Azure AI Engineer Associate AI-102 – ( $165 USD* )
• Azure Stack Hub Operator Associate AZ-600 – ( $165 USD* )
• Azure Solutions Architect Expert AZ-303 ( USD 165.00* )
• DevOps Engineer Expert AZ-400 ( USD 165.00* )
• Azure IoT Developer Specialty AZ-220 ( USD 165.00* )
• Azure for SAP Workloads Specialty AZ-120 ( USD 165.00* )

Best salary for Azure Certified Professional

The average salary of Azure Solutions Architects in the U.S. $152,142 and Rs 1,575,000 in India.
The Azure Fundamentals certification average salary is $126,653 and Rs. 9,00,000 in India.
Azure Administrator Associate average salary is $125,993 and 3.0 Lakhs to Rs 16.9 Lakhs in India.

Best Azure Certification Tutorials

https://www.tutorialspoint.com/microsoft_azure/cloud_computing_overview.htm

Best Azure Certification Video Tutorials

Best Azure certification excercise dumps

https://www.examtopics.com/exams/microsoft/az-900/view/

https://www.prepaway.com/az-104-exam.html

Best Azure certification Ebooks

https://azure.microsoft.com/en-in/blog/free-ebook-the-developer-s-guide-to-microsoft-azure-now-available/

The post Complete Azure Certification Guide & tutorials appeared first on Artificial Intelligence.

Software development Life cycle (SDLC) is a process of producing high-quality software at the lowest cost and in possibly less time. Generally, SDLC has well-tested and ready-to-use phases which provide an organization to help in creating high-quality software. ISO/IEC 12207 is an international standard of software life cycle process. This standard defines all the tasks which need to develop and maintain software. SDLC targets to produce high-quality software by meeting the expectations of clients within the time limit and in budget. It is made up of a plan which describes how to develop, maintain, alter, and improve the software.

Why we need SDLC

Basically, SDLC is a method with the process, which helps in creating high-quality software. By this you can understand the whole criteria of producing effective software, that’s why SDLC is important. Without SDLC you can’t create a standard software because it gives a standard way to produce an effective and efficient software that will run in the market with client expectations which will help him in managing his part of work. With time we update the software as per customer feedbacks to get a better result which is also a part of SDLC.

Benefits of the Software Development Lifecycle

• Forms the base for project planning.
• Helps to estimate cost and time.
• It gives the clarity of the project and the development process.
• Enhance the speed and accuracy of development progress.
• Minimizes the risks and maintenance during the project.
• Its given standard improves client relations.
• SDLC implement checks to ensure that the software is well tested before being installed in greater source code
• Developers can’t move to the next step until the prior one is completed by SDLC.

What are the SDLC phases

Software Development Life Cycle Models

Waterfall Model:-

A little too old and harsh model is the Waterfall model. It is one of the old-fashioned SDLC models that is not much preferred in the modern software development ecosystem.

The reason it is not favored much is that it runs on a very inflexible structure conditioning that the entire set of requirements should be laid down from the very beginning of a project. This limits the freedom and flexibility of the actual design and development of software.

After completing the development, the product goes through the test for meeting its initial requirements. If it is not good enough, it is to be restructured, which is a lot of work.

Usually, software development companies resist dealing with Waterfall though it still seems to be an effective model for the handful of projects.

RAD Model:-

The rapid Application Development (RAD) process is an adoption of the waterfall model. It aims to developing software in a short period. The RAD model is based on prototyping and iterative development with no specific planning involved. The process of writing the software itself involves the required planning for developing the product. The RAD model is based on the concept that a better system can be developed in less time by using focus groups to collect system requirements

• Business Modeling
• Data Modeling
• Process Modeling
• Application Generation
• Testing and Turnover

 Spiral Model:-

The spiral model is a risk-based process model. This SDLC model helps the group to adopt elements of one or more process models like waterfall, incremental, etc. The spiral technique is a combination of fast prototyping and concurrency in design and development activities. The following will explain the typical uses of a Spiral Model –

• When there is a budget compellable and risk evaluation is important.
• For intermediate to high-risk projects.
• Long-term project commitment because of probable changes to economic priorities as the requirements change with time.
• Customer is not sure of their requirements which is ordinarily the case.
• Requirements are complicated and need evaluation to get clarity.
• Some changes are expected in the product during the development cycle.

V-Model :-

In this model execution of processes happens in a sequential method in a ‘V-shape’. It is also known as ‘Verification and Validation model’. The V-Model is an Expansion of the waterfall model and is based on the association of a testing phase for each related development stage. That means for every single phase in the development cycle, there is a directly associated testing stage. This is a disciplined model and the next phase starts only after completion of the previous phase.

Incremental Model :-

The incremental model is not a distinct model. It is radically a series of waterfall cycles. The requirements are divided into groups at the initial stage of the project. For each group, the SDLC model is adhered to develop software. The SDLC process repeats with each release adding more functionality till all requirements are met.

use of  Incremental Model:-

• When the requirements are much superior.
• A project has a lengthy development program.
• When Software team are not well skilful or trained.
• When the customer demands an immediate release of the product.
• You can develop precedence requirements first.

Agile Model :-  

The agile model is a model which promotes continuous interaction of development and testing during the SDLC process of any project. The agile model is a combination of iterative and incremental process models with aims on process and customer satisfaction by continuous delivery of working software products. Agile Methods have divided the product into small incremental builds. These builds are issued in iterations. Each iteration lasts from typically one to three weeks. Every iteration involves cross-functional teams working together on various areas like

• Planning
• Requirements Analysis
• Design
• Coding
• Unit Testing and
• Acceptance Testing.

At the end of the iteration, a functional product is displayed to the customer.

Iterative Model :-

In the iterative model, the iterative process starts with the implementation of a small set of software requirements, makes  enhancements in the evolving versions till the complete system is implemented and ready to deploy on the market. In this model development of the life cycle doesn’t start with full requirements, instead, it begins with the implementation of just a part of the software, which will be reviewed to identify further requirements later. This process is repeated till the new version of the software is produced at the end.

Big bang model :- 

The big bang model comprises focusing all types of possible resources in software development and coding with little bit or no planning. This model works best for small projects with the smaller size development team who works together. It is useful in academic software projects as well. It is also an ideal model where requirements are either unknown or a final release date is not provided.

Advantages of the Big Bang Model

• This is very easy to use model
• Little bit or no planning required
• Easy to handle
• Very few resources are needed
• provides flexibility to developers

Disadvantages of the Big Bang Model

• Very High risk & uncertainty.
• Not a good model for difficult and object-oriented projects.
• Poor model for long-term and ongoing projects.
• Can become very expensive if requirements are not properly understood.

Prototype Model :-

The prototype model starts with the gathering of required information to start the development process. In this the developer meets the client, understand the purpose of software and identify the actual requirement. Then a quick design is created, focused on each aspect of the software which will be visible to the user. Then it goes ahead with the development of prototype, customer checks and try to identify if any modification needs to be done. In this step, looping occurs and better versions of prototype are created. It continuously happens being in touch with client to show him if any further requirements needs to be done.  This process remains continue till the user is satisfied. Once the user is satisfied, the prototype is converted into the actual system to deploy in market.

DevOps:-  Let’s understand. In the agile Model, both Development and testing activities were concurrent, unlike the waterfall model. It was lost on practices that didn’t come up to speed with agile practices. Due to lack of collaborations between developers ad the operations team, slow down the development process and releases. Then software companies started realizing the need for better collaboration between teams and faster delivery of software. It gave birth to the DevOps approach. DevOps enabled fast software delivery with minimum problems to fix and faster resolution of problems. The term DevOps is deprived of two words development and operations. DevOps is a practice that allows a single team to manage the whole application development life cycle, i.e. development, testing, deployment, etc. The aim of DevOps is to shorten the development life cycle. DevOps is a software development approach that helps in producing high-quality software with reliability and in less time. DevOps is a software development method that aims at communication, integration, and collaboration between IT professionals to enable continuous deployment of products.

Which SDLC Model is Best

As far I have understood, DevOps is the best model in today’s software ecosystem which provides a better development life cycle with high effectiveness and efficiency in work progress.  But it doesn’t mean rest models are not useful, they are also useful and still getting used by some organizations who feel that model is best in their work. DevOps is a practice of bringing development and operation teams together whereas, Agile refers to the continuous iterative approach, which aims at collaboration, customer feedback, small, and continuous releases. DevOps’ purpose is to manage end-to-end engineering processes. It helps in increasing an organization’s speed to deliver applications and services.  The agile purpose is to manage difficult projects. The agile development process divides the product into smaller pieces and integrates them for final testing. It can be implemented in many ways, including Scrum, XP, etc.

The post Software Development Lifecycle (SDLC) Beginners Guide appeared first on Artificial Intelligence.

Today in this technology era, data science is one progressing field these days. The strong improvements seen in computational world databases give the best analysis of users’ behaviour and pattern. The whole data science life cycle begins with analyzing a problem and giving out the solution to it. Generally, a whole process to analyze and collect data is set by data scientists. 
Data science has an immense role in the business field. It lets the HR managers job easily by automatically selecting job applicants as per their requirements by producing sales forecasts and business analytics. Data science is not only in the corporate field but also in healthcare, manufacturing, entertainment, and logistics. The best part in the process of data science scientists follows the same framework as there are always some steps in general in the process of data cycle irrespective of the specifications of the project.

Life Cycle Steps

The basic common steps taken by data scientists for each project are as follows:

• Problem Identification
  
  All data science life cycle projects start with the process of identifying problems. For setting any goal for any project, the first thing is to understand the problem we are trying to solve. Identifying the problem can be effortless for the data science life cycle. You need to come up with the problem and goal which is needed to achieve. This goal or problem will act as a base for the whole data science life cycle model.
• Choice Of Representative Sample
  
  It is crucial to pick up the right data science life cycle project, especially when it is a big data plan. Here, representative samples are created by determining the correct variable suitable for solving a problem and answering the question.
  • Data Gathering
  • It is also called data mining. Here, necessary data are collected for the project. According to the location and approach, data scientists need to decide the source for collecting data it can be collecting from mobile applications, data off websites, and third-party warehouses. Here data science team also performs another step of establishing databases that can store all the information.
• Data Cleaning
• According to the representative sample, the life cycle of data science involves transforming the collected data in the same format. Firstly, they had to find the data that is not matching then by making proper calculations and algorithms for matching it. Foul Data can lead to disappointing results. If the data is not correct, one cannot get correct results even if algorithms for examining data are perfect.
• Development of Data Model
• To meet the project goal and analyze the results, data models are developed based on what the scientist wants to achieve. What scientists want to achieve will decide the development of data science. There are distinct choices for the data model, but the ultimate aim is to generate a solution that can be utilized and analyzed to meet the project’s ultimate goal.
• Data Analysis
• The aim to conduct this step is to promote engineering. Features refer to measurable attributes -they give quantifiable results which can be used for machine learning or predictive learning. Data scientists often use several features to come at the best predictions possible.
• Data Visualization
• It is a part where the results of data are explained through tables, graphs, and charts. It assists analysts and scientists with patterns related to data. It also helps to interpret compound results for those who belong to some other background.
• Deployment

• Data scientists need to examine the system to ensure it performs the required tasks correct or provide because deployment involves making use of the results and analyze to perform predictive explanation, executing a program for ML, and contribute insights into the tools which are used in the organization that was a result of the whole study.
• Long Term Monitoring
  
  These are for projects which are continuous for the long run. Here data scientists need to design a system that mines regularly and produces data sets as variable changes in time and need extended data cleaning, data mining, and analysis.
• Re-Evaluation
  
  Re-evaluation may occur in different forms. Here, data scientists assess each step and choose if any rectification is needed to enhance the project before stepping to the next step of the whole cycle. This concludes the entire data science process life cycle.

Conclusion

These are the ten steps in the whole data science life cycle. A key skill set to have is providing a comprehensive and practical description.

The display of the data obtained and transformed must be brief and penetrable enough for the crowd. Information, data content, existing goal, and systematic method are whole, called the heart of the entire data science life cycle. Jigsaw Academy offers data science certification courses that can help you gain your data science certificate.

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Applied artificial intelligence is transforming our world with practical use cases. 

Artificial intelligence is making machines around us smarter. While this is common knowledge, what many don’t understand is that artificial intelligence is more of a concept, and applied artificial intelligence is what puts AI to work in reality. Applied AI leverages the capabilities of software applications and powers machine learning, making it highly accurate and adaptable. It is applied AI that is transforming business processes as well the modern society. 

Several benefits like accuracy, cost-saving, and better decision-making come bundled with Applied artificial intelligence. In a dynamic business landscape, these are the benefits applied AI offers to industries. 

1. Better Decision Making: A lot of tasks would happen smoothly if machines had human-like judgment capabilities and that is exactly what applied AI brings to the forefront. It ensures reduced errors, predicts close to accurate outcomes, achieves end-to-end process automation, and creates a smart ecosystem. 

2. Perfecting Machinery: Applied AI bridges the gap between the digital world and the machine world while reducing errors, social ethics, and human bias in the process. 

3. Sharp Efficiency: Throughout all the stages of business processes, Applied AI accelerates efficiency while saving time, effort, and money. 

4. Optimized Automation: Applied AI helps in automating mundane and repetitive tasks to free up employees. While computer systems powered by AI handle tedious tasks, employees can devote their time and effort elsewhere to increase the business ROI. 

5. Increased Profits: Applied AI boosts profitability by identifying and solving complex business problems, faster than humans, through its machine learning capabilities. 

Applications of Applied AI 

Applied AI is put to work in various forms, depending on its purpose. These forms include natural language generation, chatbots, speech or image recognition, and sentiment analysis. This technology has become so omnipresent that it has made its place even in the creation of CRM platforms that allow better customer handling and lead to increased customer satisfaction. Industries like marketing use applied AI to target the right advertisement to the right audience, the education industry uses applied AI to decide the right curriculum, law enforcement uses chatbots for threat detection, finance uses applied AI for analyzing trade trends, the manufacturing industry uses applied AI for logistical support, and the healthcare industry uses applied AI for early detection and disease diagnosis, amongst many other uses. 

At the rate at which artificial intelligence is advancing, applied AI will see roaring use cases in the future, which is unthinkable at the moment. It is truly one of the most phenomenal and disruptive technologies of our time with immense capabilities to transform the world as we know it.

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A deep learning algorithm could help providers predict survival expectancy in patients with lung cancer, which could help guide treatment decisions.

A deep learning tool was able to accurately predict survival expectancy in patients with lung cancer, potentially leading to more informed care decisions by providers, according to a study published in the International Journal of Medical Informatics.

The study showed that in certain conditions, the deep learning model was more than 71 percent accurate in predicting survival expectancy of lung cancer patients, compared to other machine learning models that performed with about 61 percent accuracy.

The tool can analyze a large amount of data that describe the patients and the disease to understand how a combination of factors affect lung cancer survival periods. These factors include information like types of cancer, size of tumors, speed of tumor growth, and demographic data.

“This is a high-performance system that is highly accurate and is aimed at helping doctors make these important decisions about providing care to their patients,” said Youakim Badr, associate professor of data analytics at Penn State Great Valley. “Of course, this tool can’t be used as a substitute for a doctor in making decisions on lung cancer treatments.”

Information on a patient’s survival expectancy could help guide providers and caregivers make improved decisions on using medicines, allocating resources, and determining the intensity of care for patients.

Researchers noted that deep learning techniques are uniquely suited to address lung cancer prognosis because the technology can provide the comprehensive analysis needed in cancer research.

In deep learning, developers apply a sophisticated structure of multiple layers of artificial neurons. The learning aspect of deep learning comes from how the system learns from connections between data and labels, the team noted.

“Deep learning is a machine-learning algorithm that makes associations between the data, itself, and the labels that we use to describe the data examples,” said Badr. “By making these associations, it learns from the data.”

The structure of deep learning also offers several advantages for many data science tasks, especially in cases involving large datasets.

“It improves performance tremendously. In deep learning we can go deeper, which is why they call it that. In traditional machine learning, you have a simple structure of layers of neural networks. In each layer, you have a group of cells,” said Robin G. Qiu, professor of information science and engineering and an affiliate of the Institute for Computational and Data Sciences.

“In deep learning, there are many layers of these cells that can be architected into a sophisticated structure to perform better feature transformation and extraction, which gives you the ability to further improve the accuracy of any model.”

Researchers analyzed data from the Surveillance, Epidemiology, and End Results (SEER) program. The SEER dataset is one of the biggest and most comprehensive databases on the early diagnosis information for cancer patients in the US. The program’s cancer registries cover almost 35 percent of US cancer patients.

“One of the really good things about this data is that it covers a large section of the population and it’s really diverse,” said Shreyesh Doppalapudi, a graduate-student research assistant and first author of the paper.

“Another good thing is that it covers a lot of different features, which you can use for many different purposes. This becomes very valuable, especially when using machine learning approaches.”

When the team compared several deep learning approaches to traditional machine learning models, the deep learning approaches performed much better than traditional machine learning methods.

The deep learning technique enabled researchers to find associations in the SEER dataset, which includes about 800,000 to 900,000 entries – something that would have been incredibly challenging without the assistance of AI.

“If it were only three fields I would say it would be impossible — and we had about 150 fields,” said Doppalapudi. “Understanding all of those different fields and then reading and learning from that information, would be impossible.”

Going forward, researchers will aim to improve the model and test its ability to analyze other types of cancers and medical conditions.

“The accuracy rate is good, but it’s not perfect, so part of our future work is to improve the model,” said Qiu.

Researchers also plan to connect with domain experts on specific cancers and medical conditions.

“In a lot of cases, we might not know a lot of features that should go into the model,” said Qiu. “But, by collaborating with domain experts, they could help us collect important features about patients that we might not be aware of and that would further improve the model.”

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A SHOCKING video has gone viral, of a tour guide pinning a baby elephant down into the sea, so a bikini-clad tourist can take pictures.

The mahout dragged the calf into the ocean in Phuket, southern Thailand, on May 14, after the two holidaymakers paid for rides.

One man was seen taking selfies while sitting on top of a fully grown elephant which was knee deep in the clear blue water.

A female holidaymaker in a white bikini then took pictures of the baby elephant.

The nervous creature appeared uncomfortable in the water but the mahout put his hands on the elephant’s neck and pushed it down into the sea.

As the calf waved its trunk in apparent discomfort, the mahout puts his hand on the creatures head while continuing to pin it down into the sea.

The cruel behaviour was an attempt to keep the calf still so the tourist could take a picture of it in the sea.

The woman snaps the elephant then turns the camera towards her partner, who is riding the other elephant.

The scene sparked anger from animal rights campaigners who said that taking the elephants into the sea had also damaged coral reefs in the area.

Thammarat Suwannaposri from Spotlight Phuket said: ‘’The herd were the part of tourist attraction organised by a restaurant nearby and they didn’t ask the permission to do so.

“The beach is very rocky but it is full of the old coral reef which was not allowed to be demolished according to the law. But they brought a digger to clear the area so that those elephants could go in the water and pose for pictures with tourists.

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