Epython Lab
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Welcome to Epython Lab, where you can get resources to learn, one-on-one trainings on machine learning, business analytics, and Python, and solutions for business problems.

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Natural Language Processing

Natural language processing (NLP) is the field devoted to methods and algorithms for processing human (natural) languages for computers. NLP is a vast discipline that is actively being researched. Some examples of machine learning applications using NLP include sentiment analysis, topic modeling, and language translation. In NLP, the following terms have specific meanings:

- Corpus: The body/collection of text being investigated.
- Document: The unit of analysis, what is considered a single observation.

Examples of corpora include a collection of reviews and tweets, the text of the Iliad, and Wikipedia articles. Documents can be whatever you decided, it is what your model will consider an observation. For the example when the corpus is a collection of reviews or tweets, it is logical to make the document a single review or tweet. For the example of the text of the Iliad, we can set the document size to a sentence or a paragraph. The choice of document size will be influenced by the size of our corpus. If it is large, it may make sense to call each paragraph a document. As is usually the case, some design choices that need to be made.
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ML Algorithms Cheatsheet (python and R)
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Artificial_Intelligence,_IOT_and_machine_Learning_AI_programs_using.pdf
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Artificial Intelligence, IOT and machine Learning : AI programs using Python A Beginners book

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Parameters are values while arguments are vatiables
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Default arguments are evaluated during function call.
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The value of default argument can be changed in the function body.
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Local variables can be accessible inside inner function if it is declared inside outer function.
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