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Title: GitHub - khc25/Machine-Learning-with-Python: Practice and tutorial-style notebooks covering wide variety of machine learning techniques · GitHub

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Description: Practice and tutorial-style notebooks covering wide variety of machine learning techniques - khc25/Machine-Learning-with-Python

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Datasets	https://github.com/khc25/Machine-Learning-with-Python/tree/master/Datasets
Function Approximation by Neural Network	https://github.com/khc25/Machine-Learning-with-Python/tree/master/Function%20Approximation%20by%20Neural%20Network
Function Approximation by Neural Network	https://github.com/khc25/Machine-Learning-with-Python/tree/master/Function%20Approximation%20by%20Neural%20Network
Images	https://github.com/khc25/Machine-Learning-with-Python/tree/master/Images
Images	https://github.com/khc25/Machine-Learning-with-Python/tree/master/Images
Pandas and Numpy	https://github.com/khc25/Machine-Learning-with-Python/tree/master/Pandas%20and%20Numpy
Pandas and Numpy	https://github.com/khc25/Machine-Learning-with-Python/tree/master/Pandas%20and%20Numpy
Random Function Generator	https://github.com/khc25/Machine-Learning-with-Python/tree/master/Random%20Function%20Generator
Random Function Generator	https://github.com/khc25/Machine-Learning-with-Python/tree/master/Random%20Function%20Generator
Real Dataset Problems	https://github.com/khc25/Machine-Learning-with-Python/tree/master/Real%20Dataset%20Problems
Real Dataset Problems	https://github.com/khc25/Machine-Learning-with-Python/tree/master/Real%20Dataset%20Problems
Synthetic_data_generation	https://github.com/khc25/Machine-Learning-with-Python/tree/master/Synthetic_data_generation
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Interactive ML-1.ipynb	https://github.com/khc25/Machine-Learning-with-Python/blob/master/Interactive%20ML-1.ipynb
Interactive ML-1.ipynb	https://github.com/khc25/Machine-Learning-with-Python/blob/master/Interactive%20ML-1.ipynb
Jupyter_Markdown_Primer.ipynb	https://github.com/khc25/Machine-Learning-with-Python/blob/master/Jupyter_Markdown_Primer.ipynb
Jupyter_Markdown_Primer.ipynb	https://github.com/khc25/Machine-Learning-with-Python/blob/master/Jupyter_Markdown_Primer.ipynb
LICENSE	https://github.com/khc25/Machine-Learning-with-Python/blob/master/LICENSE
LICENSE	https://github.com/khc25/Machine-Learning-with-Python/blob/master/LICENSE
Linear_Regression_Methods.ipynb	https://github.com/khc25/Machine-Learning-with-Python/blob/master/Linear_Regression_Methods.ipynb
Linear_Regression_Methods.ipynb	https://github.com/khc25/Machine-Learning-with-Python/blob/master/Linear_Regression_Methods.ipynb
Linear_Regression_Practice.ipynb	https://github.com/khc25/Machine-Learning-with-Python/blob/master/Linear_Regression_Practice.ipynb
Linear_Regression_Practice.ipynb	https://github.com/khc25/Machine-Learning-with-Python/blob/master/Linear_Regression_Practice.ipynb
Multi-variate LASSO regression with CV.ipynb	https://github.com/khc25/Machine-Learning-with-Python/blob/master/Multi-variate%20LASSO%20regression%20with%20CV.ipynb
Multi-variate LASSO regression with CV.ipynb	https://github.com/khc25/Machine-Learning-with-Python/blob/master/Multi-variate%20LASSO%20regression%20with%20CV.ipynb
README.md	https://github.com/khc25/Machine-Learning-with-Python/blob/master/README.md
README.md	https://github.com/khc25/Machine-Learning-with-Python/blob/master/README.md
Random_Forest_Regression_Practice.ipynb	https://github.com/khc25/Machine-Learning-with-Python/blob/master/Random_Forest_Regression_Practice.ipynb
Random_Forest_Regression_Practice.ipynb	https://github.com/khc25/Machine-Learning-with-Python/blob/master/Random_Forest_Regression_Practice.ipynb
Regularized polynomial regression with linear and random sampling.ipynb	https://github.com/khc25/Machine-Learning-with-Python/blob/master/Regularized%20polynomial%20regression%20with%20linear%20and%20random%20sampling.ipynb
Regularized polynomial regression with linear and random sampling.ipynb	https://github.com/khc25/Machine-Learning-with-Python/blob/master/Regularized%20polynomial%20regression%20with%20linear%20and%20random%20sampling.ipynb
_config.yml	https://github.com/khc25/Machine-Learning-with-Python/blob/master/_config.yml
_config.yml	https://github.com/khc25/Machine-Learning-with-Python/blob/master/_config.yml
README	https://github.com/khc25/Machine-Learning-with-Python
BSD-2-Clause license	https://github.com/khc25/Machine-Learning-with-Python
	https://github.com/khc25/Machine-Learning-with-Python#python-machine-learning-notebooks-tutorial-style
You can connect with me on LinkedIn here	https://www.linkedin.com/in/tirthajyoti-sarkar-2127aa7
	https://github.com/khc25/Machine-Learning-with-Python#dr-tirthajyoti-sarkar-sunnyvale-ca-you-can-connect-with-me-on-linkedin-here
	https://camo.githubusercontent.com/83beec85483ed4954a90e45f0c113c5ecead75a4e2e0ebe8e7286fe1f7aff7df/68747470733a2f2f636f6f6b69656567726f75702e636f6d2f77702d636f6e74656e742f75706c6f6164732f323031382f31302f322d312e706e67
"Some Essential Hacks and Tricks for Machine Learning with Python"	https://heartbeat.fritz.ai/some-essential-hacks-and-tricks-for-machine-learning-with-python-5478bc6593f2
	https://github.com/khc25/Machine-Learning-with-Python#some-essential-hacks-and-tricks-for-machine-learning-with-python
	https://github.com/khc25/Machine-Learning-with-Python#essential-tutorial-type-notebooks-on-pandas-and-numpy
Basics of Numpy array	https://github.com/tirthajyoti/PythonMachineLearning/blob/master/Pandas%20and%20Numpy/Basics%20of%20Numpy%20arrays.ipynb
Basics of Pandas DataFrame	https://github.com/tirthajyoti/PythonMachineLearning/blob/master/Pandas%20and%20Numpy/Basics%20of%20Pandas%20DataFrame.ipynb
Basics of Matplotlib and Descriptive Statistics	https://github.com/tirthajyoti/PythonMachineLearning/blob/master/Pandas%20and%20Numpy/Basics%20of%20Matplotlib%20and%20Descriptive%20Statistics.ipynb
	https://github.com/khc25/Machine-Learning-with-Python#tutorial-type-notebooks-covering-regression-classification-clustering-dimensionality-reduction-and-some-basic-neural-network-algorithms
	https://github.com/khc25/Machine-Learning-with-Python#regression
	https://camo.githubusercontent.com/a20fd15968101c92a47a759f0cf49478573df42022527f586bae132e7a89e463/68747470733a2f2f736c696465706c617965722e636f6d2f736c6964652f363035333138322f32302f696d616765732f31302f53696d706c652b4c696e6561722b52656772657373696f6e2b4d6f64656c2e6a7067
check the article I wrote on freeCodeCamp	https://medium.freecodecamp.org/data-science-with-python-8-ways-to-do-linear-regression-and-measure-their-speed-b5577d75f8b
	https://camo.githubusercontent.com/19dff5115626989d03b2837408d408331b67126f9f576da8f6c55c15217c0648/68747470733a2f2f75706c6f61642e77696b696d656469612e6f72672f77696b6970656469612f636f6d6d6f6e732f7468756d622f662f66382f4c315f616e645f4c325f62616c6c732e7376672f33303070782d4c315f616e645f4c325f62616c6c732e7376672e706e67
check the article I wrote on Towards Data Science	https://towardsdatascience.com/machine-learning-with-python-easy-and-robust-method-to-fit-nonlinear-data-19e8a1ddbd49
	https://github.com/khc25/Machine-Learning-with-Python#classification
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check the article I wrote in Towards Data Science on SVM and sorting algorithm	https://towardsdatascience.com/how-the-good-old-sorting-algorithm-helps-a-great-machine-learning-technique-9e744020254b
	https://camo.githubusercontent.com/c0a88222f380708c67b7daf06ef8c4e5381fae00699fdd98c0d8aac8c0d79afd/68747470733a2f2f646f63732e6f70656e63762e6f72672f322e342f5f696d616765732f6f7074696d616c2d6879706572706c616e652e706e67
	https://github.com/khc25/Machine-Learning-with-Python#clustering
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	https://github.com/khc25/Machine-Learning-with-Python#dimensionality-reduction
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	https://github.com/khc25/Machine-Learning-with-Python#deep-learningneural-network
	https://github.com/khc25/Machine-Learning-with-Python#random-data-generation-using-symbolic-expressions
Sympy package	https://www.sympy.org/en/index.html
Random regression and classification problem generation with symbolic expression	https://towardsdatascience.com/random-regression-and-classification-problem-generation-with-symbolic-expression-a4e190e37b8d
Readme	https://github.com/khc25/Machine-Learning-with-Python#readme-ov-file
BSD-2-Clause license	https://github.com/khc25/Machine-Learning-with-Python#BSD-2-Clause-1-ov-file
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