Introduction to AI and Machine Learning

https://www.linkedin.com/pulse/introduction-ai-machine-learning-ian-rowan/ “Artificial Intelligence” is a term ubiquitous in today’s media and is used in some of the most unique applications to make business and life more efficient and logical. Most of whom hear this term minds’ typically shoot towards robots, sci-fi films, and most realistically, autonomous vehicles. This is a common misconception that arises from

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Top 5 Python Libraries for Data Visualization

Data visualization is a pictorial or graphical format of the presentation of data. This graphical representation helps  decision makers to see analytics presented visually. So, they can get difficult concepts and identify new patterns easily form the data. On the other way interactive data visualization helps to drill down into charts and graphs to get  more

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Python Deep Learning tutorial: Create a GRU (RNN) and Elman RNN implementation in TensorFlow

MLPs (Multi-Layer Perceptrons) are great for many classification and regression tasks. However, it is hard for MLPs to do classification and regression on sequences. In this Python deep learning tutorial, a GRU is implemented in TensorFlow. Tensorflow is one of the many Python Deep Learning libraries. https://www.data-blogger.com/2017/08/27/gru-implementation-tensorflow/ In this Python Deep Learning tutorial, an implementation and explanation

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Edge Analytics : What, Why, When, Who, Where , How

Edge analytics is an exciting area with organizations in Industrial Internet Of Things (IIOT) area increasing their investments year over year. Leading vendor companies are aggressively investing into this fast growing area In specific segments such as retail, manufacturing, energy, and logistics, edge analytics delivers quantifiable business benefits by reducing latency of decisions, scaling out

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Life Cycle of a Data Science Project

https://www.dezyre.com/article/life-cycle-of-a-data-science-project/270#39_1443 When working with big data, it is always advantageous for data scientists to follow a well-defined data science workflow. Regardless of whether a data scientist wants to perform analysis with the motive of conveying a story through data visualization or wants to build a data model- the data science workflow process matters. Having a standard workflow

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What is Big Data? A buzzword explained

https://www.scnsoft.com/blog/what-is-big-data   For years, people ask all-knowing Google how big data can help businesses to succeed, what big data technologies are the best, and a wide range of other important questions. A lot has been written and said about big data already, but the term itself remains unexplained. To be fair, we do not count

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