Hello, everyone.
Following are first 2 weeks of this series. You can find them on my github repository. You can run all the notebook on colab or jupyter as well.
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Topic : Data Types, Strings, Operators, Chaining Comparison Operators with Logical Operators
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Topic : Python Lists and Dictionaries, Sets, Tuples and etc
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Topic : Loop, Break and Continue Statement, Object-Oriented Programming and Class
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Day 4 - Intermediate Python Part1
Topic : First Class Function, Private variables, Global and Non Local variables, Magic Function, Tuple Unpacking, Static Variables and Method
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Day 5 - Intermediate Python Part2
Topic : Lambda function, Matic methods, Inheritance and Polymorphism, Erros and Exception Handling, User-defined function, Python garbage collection, and debugger
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Topic : Decorators, Memoization using Decorators, Generators, Ordered and Defaultdict, Coroutine
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Day 7 - Statistics for Data Science and Machine Learning
Topic : Statistics for Data Science
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Day 8 - Maths for Data Science and Machine Learning
Topic : Linear Algebra, Calculus, Matrix and Vectors, Bayes Theorem and Cheatsheets
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Topic : Pandas Series, DataFrame
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Topic : Indexing, Filtering, Transformation, Merging, Hierarchial Indexing
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Topic : Flattening, Concatenation and Broadcasting
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Day 12 - Data PreProcessing Part1
Topic : Encoding categorical data, Split data, Feature Scaling
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Day 13 - Data PreProcessing Part2
Topic : Data Cleaning, Data Augmentation, Transformatoin, Channel Shift
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Topic : Simple Linear Regression, Multi Linear Regression, Polynomial Regression
Hope my work would be little bit helpful for AI enthusiastic.
If that, please star that repository then follow me on Github and Dev.to
https://dev.to/levintech
https://github.com/levintech
Best Regards.
Top comments (2)
Hi.. Is it okay to follow this path as a beginner?
In case of you are absolutely beginner who has not programming experience, it will not suitable for you. Once you basically familiar python and you can try this series.