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

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"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
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https://patch-diff.githubusercontent.com/codemacs/Machine-Learning-with-Python#essential-tutorial-type-notebooks-on-pandas-and-numpy
Basics of Numpy arrayhttps://github.com/tirthajyoti/PythonMachineLearning/blob/master/Pandas%20and%20Numpy/Basics%20of%20Numpy%20arrays.ipynb
Basics of Pandas DataFramehttps://github.com/tirthajyoti/PythonMachineLearning/blob/master/Pandas%20and%20Numpy/Basics%20of%20Pandas%20DataFrame.ipynb
Basics of Matplotlib and Descriptive Statisticshttps://github.com/tirthajyoti/PythonMachineLearning/blob/master/Pandas%20and%20Numpy/Basics%20of%20Matplotlib%20and%20Descriptive%20Statistics.ipynb
https://patch-diff.githubusercontent.com/codemacs/Machine-Learning-with-Python#tutorial-type-notebooks-covering-regression-classification-clustering-dimensionality-reduction-and-some-basic-neural-network-algorithms
https://patch-diff.githubusercontent.com/codemacs/Machine-Learning-with-Python#regression
https://camo.githubusercontent.com/a20fd15968101c92a47a759f0cf49478573df42022527f586bae132e7a89e463/68747470733a2f2f736c696465706c617965722e636f6d2f736c6964652f363035333138322f32302f696d616765732f31302f53696d706c652b4c696e6561722b52656772657373696f6e2b4d6f64656c2e6a7067
Multiple ways to perform linear regression in Python and their speed comparisonhttps://github.com/tirthajyoti/Machine-Learning-with-Python/blob/master/Regression/Linear_Regression_Methods.ipynb
check the article I wrote on freeCodeCamphttps://medium.freecodecamp.org/data-science-with-python-8-ways-to-do-linear-regression-and-measure-their-speed-b5577d75f8b
Multi-variate regression with regularizationhttps://github.com/tirthajyoti/Machine-Learning-with-Python/blob/master/Regression/Multi-variate%20LASSO%20regression%20with%20CV.ipynb
https://camo.githubusercontent.com/19dff5115626989d03b2837408d408331b67126f9f576da8f6c55c15217c0648/68747470733a2f2f75706c6f61642e77696b696d656469612e6f72672f77696b6970656469612f636f6d6d6f6e732f7468756d622f662f66382f4c315f616e645f4c325f62616c6c732e7376672f33303070782d4c315f616e645f4c325f62616c6c732e7376672e706e67
check the article I wrote on Towards Data Sciencehttps://towardsdatascience.com/machine-learning-with-python-easy-and-robust-method-to-fit-nonlinear-data-19e8a1ddbd49
Detailed visual analytics and goodness-of-fit diagnostic tests for a linear regression problemhttps://github.com/tirthajyoti/Machine-Learning-with-Python/blob/master/Regression/Regression_Diagnostics.ipynb
https://patch-diff.githubusercontent.com/codemacs/Machine-Learning-with-Python#classification
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check the article I wrote in Towards Data Science on SVM and sorting algorithmhttps://towardsdatascience.com/how-the-good-old-sorting-algorithm-helps-a-great-machine-learning-technique-9e744020254b
https://camo.githubusercontent.com/c0a88222f380708c67b7daf06ef8c4e5381fae00699fdd98c0d8aac8c0d79afd/68747470733a2f2f646f63732e6f70656e63762e6f72672f322e342f5f696d616765732f6f7074696d616c2d6879706572706c616e652e706e67
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https://patch-diff.githubusercontent.com/codemacs/Machine-Learning-with-Python#deep-learningneural-network
Demo notebook to illustrate the superiority of deep neural network for complex nonlinear function approximation taskhttps://github.com/tirthajyoti/Machine-Learning-with-Python/blob/master/Function%20Approximation%20by%20Neural%20Network/Polynomial%20regression%20-%20linear%20and%20neural%20network.ipynb
https://patch-diff.githubusercontent.com/codemacs/Machine-Learning-with-Python#random-data-generation-using-symbolic-expressions
Sympy packagehttps://www.sympy.org/en/index.html
Random regression and classification problem generation with symbolic expressionhttps://towardsdatascience.com/random-regression-and-classification-problem-generation-with-symbolic-expression-a4e190e37b8d
Simple deployment examples (serving ML models on web API)https://github.com/tirthajyoti/Machine-Learning-with-Python/tree/master/Deployment
https://patch-diff.githubusercontent.com/codemacs/Machine-Learning-with-Python#simple-deployment-examples-serving-ml-models-on-web-api
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