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Function Approximation by Neural Networkhttps://github.com/gdev701/Machine-Learning-with-Python/tree/docs/Function%20Approximation%20by%20Neural%20Network
Function Approximation by Neural Networkhttps://github.com/gdev701/Machine-Learning-with-Python/tree/docs/Function%20Approximation%20by%20Neural%20Network
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Pandas and Numpyhttps://github.com/gdev701/Machine-Learning-with-Python/tree/docs/Pandas%20and%20Numpy
Pandas and Numpyhttps://github.com/gdev701/Machine-Learning-with-Python/tree/docs/Pandas%20and%20Numpy
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Real Dataset Problemshttps://github.com/gdev701/Machine-Learning-with-Python/tree/docs/Real%20Dataset%20Problems
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https://github.com/tirthajyoti/Machine-Learning-with-Python/network
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https://github.com/gdev701/Machine-Learning-with-Python/tree/docs#python-machine-learning-notebooks-tutorial-style
Please feel free to add me on LinkedIn herehttps://www.linkedin.com/in/tirthajyoti-sarkar-2127aa7
https://github.com/gdev701/Machine-Learning-with-Python/tree/docs#dr-tirthajyoti-sarkar-fremont-ca-please-feel-free-to-add-me-on-linkedin-here
https://github.com/gdev701/Machine-Learning-with-Python/tree/docs#requirements
"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/gdev701/Machine-Learning-with-Python/tree/docs#some-essential-hacks-and-tricks-for-machine-learning-with-python
https://camo.githubusercontent.com/83beec85483ed4954a90e45f0c113c5ecead75a4e2e0ebe8e7286fe1f7aff7df/68747470733a2f2f636f6f6b69656567726f75702e636f6d2f77702d636f6e74656e742f75706c6f6164732f323031382f31302f322d312e706e67
https://github.com/gdev701/Machine-Learning-with-Python/tree/docs#essential-tutorial-type-notebooks-on-pandas-and-numpy
Basic Numpy operationshttps://github.com/tirthajyoti/Machine-Learning-with-Python/blob/master/Pandas%20and%20Numpy/Basics%20of%20Numpy%20arrays.ipynb
https://github.com/gdev701/Machine-Learning-with-Python/tree/docs#basic-numpy-operations
Basic Pandas operationshttps://github.com/tirthajyoti/Machine-Learning-with-Python/blob/master/Pandas%20and%20Numpy/Basics%20of%20Pandas%20DataFrame.ipynb
https://github.com/gdev701/Machine-Learning-with-Python/tree/docs#basic-pandas-operations
Basics of visualization with Matplotlib and descriptive statshttps://github.com/tirthajyoti/Machine-Learning-with-Python/blob/master/Pandas%20and%20Numpy/Basics%20of%20Matplotlib%20and%20Descriptive%20Statistics.ipynb
https://github.com/gdev701/Machine-Learning-with-Python/tree/docs#basics-of-visualization-with-matplotlib-and-descriptive-stats
Advanced Pandas operationshttps://github.com/tirthajyoti/Machine-Learning-with-Python/blob/master/Pandas%20and%20Numpy/Advanced%20Pandas%20Operations.ipynb
https://github.com/gdev701/Machine-Learning-with-Python/tree/docs#advanced-pandas-operations
How to read various data sourceshttps://github.com/tirthajyoti/Machine-Learning-with-Python/blob/master/Pandas%20and%20Numpy/Read_data_various_sources/How%20to%20read%20various%20sources%20in%20a%20DataFrame.ipynb
https://github.com/gdev701/Machine-Learning-with-Python/tree/docs#how-to-read-various-data-sources
PDF reading and table processing demohttps://github.com/tirthajyoti/Machine-Learning-with-Python/blob/master/Pandas%20and%20Numpy/Read_data_various_sources/PDF%20table%20reading%20and%20processing%20demo.ipynb
https://github.com/gdev701/Machine-Learning-with-Python/tree/docs#pdf-reading-and-table-processing-demo
How fast are Numpy operations compared to pure Python code?https://github.com/tirthajyoti/Machine-Learning-with-Python/blob/master/Pandas%20and%20Numpy/How%20fast%20are%20NumPy%20ops.ipynb
articlehttps://towardsdatascience.com/why-you-should-forget-for-loop-for-data-science-code-and-embrace-vectorization-696632622d5f
https://github.com/gdev701/Machine-Learning-with-Python/tree/docs#how-fast-are-numpy-operations-compared-to-pure-python-code-read-my-article-on-medium-related-to-this-topic
Fast reading from Numpy using .npy file formathttps://github.com/tirthajyoti/Machine-Learning-with-Python/blob/master/Pandas%20and%20Numpy/Numpy_Reading.ipynb
articlehttps://towardsdatascience.com/why-you-should-start-using-npy-file-more-often-df2a13cc0161
https://github.com/gdev701/Machine-Learning-with-Python/tree/docs#fast-reading-from-numpy-using-npy-file-format-read-my-article-on-medium-on-this-topic
https://github.com/gdev701/Machine-Learning-with-Python/tree/docs#tutorial-type-notebooks-covering-regression-classification-clustering-dimensionality-reduction-and-some-basic-neural-network-algorithms
https://github.com/gdev701/Machine-Learning-with-Python/tree/docs#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://github.com/gdev701/Machine-Learning-with-Python/tree/docs#classification
https://camo.githubusercontent.com/203433cd3bf1cb146836c0be530ec0166f92c17f944419ac00de15e9b5309f8a/68747470733a2f2f7170682e66732e71756f726163646e2e6e65742f6d61696e2d71696d672d3931346232396537373765373862343462363732343662363661346436643731
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
https://github.com/gdev701/Machine-Learning-with-Python/tree/docs#clustering
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https://github.com/gdev701/Machine-Learning-with-Python/tree/docs#dimensionality-reduction
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https://github.com/gdev701/Machine-Learning-with-Python/tree/docs#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://github.com/gdev701/Machine-Learning-with-Python/tree/docs#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
https://github.com/gdev701/Machine-Learning-with-Python/tree/docs#simple-deployment-examples-serving-ml-models-on-web-api
Serving a linear regression model through a simple HTTP server interfacehttps://github.com/tirthajyoti/Machine-Learning-with-Python/tree/master/Deployment/Linear_regression
Serving a recurrent neural network (RNN) through a HTTP webpagehttps://github.com/tirthajyoti/Machine-Learning-with-Python/tree/master/Deployment/rnn_app
https://github.com/gdev701/Machine-Learning-with-Python/tree/docs#object-oriented-programming-with-machine-learning
building your own Scikit-learn-like estimator, and making it betterhttps://github.com/tirthajyoti/Machine-Learning-with-Python/blob/master/OOP_in_ML/Class_MyLinearRegression.ipynb
Object-oriented programming for data scientists: Build your ML estimatorhttps://towardsdatascience.com/object-oriented-programming-for-data-scientists-build-your-ml-estimator-7da416751f64
How a simple mix of object-oriented programming can sharpen your deep learning prototypehttps://towardsdatascience.com/how-a-simple-mix-of-object-oriented-programming-can-sharpen-your-deep-learning-prototype-19893bd969bd
machine-learning-with-python.readthedocs.io/en/latest/https://machine-learning-with-python.readthedocs.io/en/latest/
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