Source – https://www.analyticsinsight.net/ The hype for highest paying companies for Data Scientists attracts more Aspirants The data science landscape is filled with opportunities spanning diverse industries. As new technologies are being added to the digital sphere year-on-year, the transformation is likely to continue into the coming decade. Owing to the increasing influence of technology in our daily Read More

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Source – https://www.analyticsinsight.net/ Data scientists and RPA developers should collaborate to make a perfect team. If  RPA developers work with data scientists, it will facilitate more creative solutions to complex business problems; than working separately. Robotic process automation (RPA) is a cost-effective way of automating basic tasks as humans do, with the help of various hardware and software systems that can perform on Read More

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Source – https://analyticsindiamag.com/ Emerging technologies like AI, data science and machine learning are all about working with intelligent models that need good algorithms to run. For instance, logistic regression or support vector machines.To understand these algorithms and how they work, one must be adept at programming languages. Here, we discuss 11 crucial programming languages for data scientists. 1| Read More

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Source: analyticsinsight.net How to add value to businesses with the help of an AI Factory? Like a physical factory creates physical products reliably at scale and speed, an artificial intelligence (AI) factory delivers AI solutions for businesses at scale and speed. An AI factory combines data, people, process, product, and platform to move beyond science experiments and deliver Read More

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Source: analyticsinsight.net Data scientists need to assemble predictive analytics workflow benefits to review on processes and algorithms. Data science techniques and tools are constantly evolving and only online resources can aid data scientists to keep up the pace. Even though when traditional models like reading books and journals give the understanding of fundamental concepts that benefit data scientists on a large-scale. The Read More

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Source: analyticsinsight.net What makes Python a top choice in the Data Science community? Python has become the most used programming language for data science practices. Developed by Guido van Rossum and launched in 1991, it is an interactive and object-oriented programming language similar to PERL or Ruby. Its inherent readability, simplicity, clean visual layout, less syntactic exceptions, greater string manipulation, Read More

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Source: techcrunch.com Data science is the name of the game these days for companies that want to improve their decision making by tapping the information they are already amassing in their apps and other systems. And today, a startup called Mode Analytics, which has built a platform incorporating machine learning, business intelligence and big data analytics Read More

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Source: infoq.com Feature Store is a core part of next generation ML platforms that empowers data scientists to accelerate the delivery of ML applications. It enables the teams to track and share features with versioning enabled and serve features for model training, batch, and real-time predictions. Mike Del Balso from Tecton.ai and Geoff Sims from Atlassian recently spoke at Spark Read More

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Source: datanami.com “We were disappointed, if not surprised, to see that data wrangling still takes the lion’s share of time in a typical data professional’s day,” Anaconda wrote in its report, “2020 State of Data Science: Moving From Hype Toward Maturity.” “Data preparation and cleansing takes valuable time away from real data science work and has a Read More

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Source: techrepublic.com Differential privacy has become an integral way for data scientists to learn from the majority of their data while simultaneously ensuring that those results do not allow any individual’s data to be distinguished or re-identified. To help more researchers with their work, IBM released the open-source Differential Privacy Library. The library “boasts a suite Read More

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Source: expresscomputer.in Data science is an industry purely driven by technology, and has gained inexplicable traction across the globe in recent times. The data science sector’s market size is expected to reach a whopping USD 140.9 billion by 2024. Businesses are looking at leveraging data to increase efficiency. Data science and analytics have flourished into Read More

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Source: analyticsinsight.net Having knowledge is not enough to survive, for survival, and for assured victory, one needs to test his/her capabilities. To test wisdom and capabilities, competitions are extremely beneficial. In the case of data science, data scientists mostly work theoretically and get rare chance to experiment with real-world data themselves. With data science competitions Read More

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Source: analyticsinsight.net Today, with the increasing volume of data day by day, processing and analysis of that data have become significant. This is where data scientists come into the scenario, determining the right data sets and variables and deriving actionable insights from that. Data scientists are analytical data experts and their roles can vary organization to organization Read More

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Source: analyticsinsight.net Quick developments in the space of machine learning and deep learning have brought about cutting-edge algorithms. These advanced algorithms are equipped for changing companies to determine multi-fold business value. Companies have begun putting resources into data science teams to lead the digital transformation journey to be at the highest point of their game. Read More

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Source: searchbusinessanalytics.techtarget.com Whether you’re newly entering the workforce, have been recently laid off, are worried about keeping your current job or have been temporarily furloughed and have some time on your hands, there’s no better time to pick up some AI-related skills than right now. According to LinkedIn, artificial intelligence and machine learning jobs have grown 74% Read More

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Source: techcrunch.com Three former Uber  engineers, who helped build the company’s Michelangelo machine learning platform, left the company last year to form Tecton.ai and build an operational machine learning platform for everyone else. Today the company announced a $20 million Series A from a couple of high-profile investors. Andreessen Horowitz  and Sequoia Capital co-led the round with Martin Casado, general partner Read More

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Source: analyticsindiamag.com The TensorFlow team at Google recently introduced a new tool for TensorFlow Lite (TFLite) known as Model Maker. The TFLite Model Maker simplifies the process of adapting and converting a TensorFlow Neural Network model to particular input data when deploying this model for on-device ML applications. Developed by researchers and engineers from the Google Brain Read More

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Source: venturebeat.com MindsDB today announced it has raised $3 million to grow its automated machine learning platform made for data scientists and developers to quickly train and deploy models. The open source platform has been downloaded more than 250,000 times through Python pip installs or software with a graphic user interface and has been used by Read More

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