Explainable AI (XAI) are a set of tools and techniques that help to make the machine learning models more interpretable. It helps in decision-making of models. Some of the packages which are part of XAI are: SHAP, LIME, Interpret ML etc. Shapash is a new library which helps in the interpretability of data science models. […]
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TensorFlow and PyTorch are two of the most popular frameworks in deep learning. Both are open-source software. TensorFlow is based on Theano and is developed by Google’s brain team. PyTorch on the other hand is based on Torch and was initialized in Facebook’s AI Research Lab. Ease of Use TensorFlow was a low-level deep learning
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Julia is one of those languages suitable for machine learning (ML) as well as deep learning (DL). Started in 2015, it is a low-level systems programming language. Like all other languages, Julia was introduced to overcome the shortcomings of the predecessors. . Features of Julia Julia can handle mathematical expressions with great ease and speed.
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R is actually a programming environment and language made specifically for graphical applications and statistical computations. R is a very unique language and has some really interesting features which aren’t present in other languages. This makes it a quite popular choice for Data Scientists. R is used for statistical computations, data analysis and graphical representation
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Python has become an integral tool used by data analysts nowadays. Every tool has some packages and libraries’ add-ins, which helps in different analysis. One such vital library in Python is the Pandas. It provides relational data in a labeled and easy-to-comprehend format. It helps in manipulating and analyzing data. Origin of Pandas The name
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Error-free and easy coding is a prerequisite for a data analyst.Thus, apart from business sense, a bit of coding with any of the available tools is mandatory. Be it SAS, R or Python. Again, if we compare among these three, SAS has comprehensive documentation and comes with a cost. R is a low-level programming language,
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Cost Effectiveness SAS is a commercial analytics software whereas R is open source hence, it is more accessible to new users. On the other hand, SAS is expensive licensed software but has an excellent support especially in critical areas and delicate scenarios where there is no room for experimentation, SAS has proven itself to be
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