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https://github.com/DeepLearningCode/100-Days-Of-ML-Code#100-days-of-ml-code
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herehttps://github.com/Avik-Jain/100-Days-Of-ML-Code/tree/master/datasets
https://github.com/DeepLearningCode/100-Days-Of-ML-Code#data-preprocessing--day-1
herehttps://github.com/Avik-Jain/100-Days-Of-ML-Code/blob/master/Code/Day%201_Data%20PreProcessing.md
https://github.com/Avik-Jain/100-Days-Of-ML-Code/blob/master/Info-graphs/Day%201.jpg
https://github.com/DeepLearningCode/100-Days-Of-ML-Code#simple-linear-regression--day-2
herehttps://github.com/Avik-Jain/100-Days-Of-ML-Code/blob/master/Code/Day2_Simple_Linear_Regression.md
https://github.com/Avik-Jain/100-Days-Of-ML-Code/blob/master/Info-graphs/Day%202.jpg
https://github.com/DeepLearningCode/100-Days-Of-ML-Code#multiple-linear-regression--day-3
herehttps://github.com/Avik-Jain/100-Days-Of-ML-Code/blob/master/Code/Day3_Multiple_Linear_Regression.md
https://github.com/Avik-Jain/100-Days-Of-ML-Code/blob/master/Info-graphs/Day%203.jpg
https://github.com/DeepLearningCode/100-Days-Of-ML-Code#logistic-regression--day-4
https://github.com/Avik-Jain/100-Days-Of-ML-Code/blob/master/Info-graphs/Day%204.jpg
https://github.com/DeepLearningCode/100-Days-Of-ML-Code#logistic-regression--day-5
https://github.com/DeepLearningCode/100-Days-Of-ML-Code#implementing-logistic-regression--day-6
herehttps://github.com/Avik-Jain/100-Days-Of-ML-Code/blob/master/Code/Day%206%20Logistic%20Regression.md
https://github.com/DeepLearningCode/100-Days-Of-ML-Code#k-nearest-neighbours--day-7
https://github.com/Avik-Jain/100-Days-Of-ML-Code/blob/master/Info-graphs/Day%207.jpg
https://github.com/DeepLearningCode/100-Days-Of-ML-Code#math-behind-logistic-regression--day-8
https://towardsdatascience.com/logistic-regression-detailed-overview-46c4da4303bchttps://towardsdatascience.com/logistic-regression-detailed-overview-46c4da4303bc
https://github.com/DeepLearningCode/100-Days-Of-ML-Code#support-vector-machines--day-9
https://github.com/DeepLearningCode/100-Days-Of-ML-Code#svm-and-knn--day-10
https://github.com/DeepLearningCode/100-Days-Of-ML-Code#implementation-of-k-nn--day-11
https://github.com/DeepLearningCode/100-Days-Of-ML-Code#support-vector-machines--day-12
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https://github.com/DeepLearningCode/100-Days-Of-ML-Code#naive-bayes-classifier-and-black-box-machine-learning--day-15
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https://github.com/DeepLearningCode/100-Days-Of-ML-Code#implemented-svm-using-kernel-trick--day-16
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https://github.com/DeepLearningCode/100-Days-Of-ML-Code#deep-learning-specialization-on-coursera--day-18
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here.https://github.com/Avik-Jain/100-Days-Of-ML-Code/blob/master/Code/Day%2034%20Random_Forest.md
https://github.com/DeepLearningCode/100-Days-Of-ML-Code#but-what-is-a-neural-network--deep-learning-chapter-1---day-35
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Computation on NumPy Arrays: Universal Functionshttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.03-Computation-on-arrays-ufuncs.ipynb
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https://github.com/DeepLearningCode/100-Days-Of-ML-Code#digging-deeper--numpy--day-47
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Structured Data: NumPy's Structured Arrayshttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.09-%3Cbr%3EStructured-Data-NumPy.ipynb
https://github.com/DeepLearningCode/100-Days-Of-ML-Code#digging-deeper--pandas--day-48
Data Manipulation with Pandashttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.00-Introduction-to-Pandas.ipynb
Introducing Pandas Objectshttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.01-Introducing-Pandas-Objects.ipynb
Data Indexing and Selectionhttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.02-Data-Indexing-and-Selection.ipynb
Operating on Data in Pandashttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.03-Operations-in-Pandas.ipynb
Handling Missing Datahttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.04-Missing-Values.ipynb
Hierarchical Indexinghttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.05-Hierarchical-Indexing.ipynb
Combining Datasets: Concat and Appendhttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.06-Concat-And-Append.ipynb
https://github.com/DeepLearningCode/100-Days-Of-ML-Code#digging-deeper--pandas--day-49
Combining Datasets: Merge and Joinhttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.07-Merge-and-Join.ipynb
Aggregation and Groupinghttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.08-Aggregation-and-Grouping.ipynb
Pivot Tableshttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.09-Pivot-Tables.ipynb
https://github.com/DeepLearningCode/100-Days-Of-ML-Code#digging-deeper--pandas--day-50
Vectorized String Operationshttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.10-Working-With-Strings.ipynb
Working with Time Serieshttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.11-Working-with-Time-Series.ipynb
High-Performance Pandas: eval() and query()https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.12-Performance-Eval-and-Query.ipynb
https://github.com/DeepLearningCode/100-Days-Of-ML-Code#digging-deeper--matplotlib--day-51
Visualization with Matplotlibhttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.00-Introduction-To-Matplotlib.ipynb
Simple Line Plotshttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.01-Simple-Line-Plots.ipynb
Simple Scatter Plotshttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.02-Simple-Scatter-Plots.ipynb
Visualizing Errorshttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.03-Errorbars.ipynb
Density and Contour Plotshttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.04-Density-and-Contour-Plots.ipynb
https://github.com/DeepLearningCode/100-Days-Of-ML-Code#digging-deeper--matplotlib--day-52
Histograms, Binnings, and Densityhttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.05-Histograms-and-Binnings.ipynb
Customizing Plot Legendshttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.06-Customizing-Legends.ipynb
Customizing Colorbarshttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.07-Customizing-Colorbars.ipynb
Multiple Subplotshttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.08-Multiple-Subplots.ipynb
Text and Annotationhttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.09-Text-and-Annotation.ipynb
https://github.com/DeepLearningCode/100-Days-Of-ML-Code#digging-deeper--matplotlib--day-53
Three-Dimensional Plotting in Matplotlibhttps://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/04.12-Three-Dimensional-Plotting.ipynb
https://github.com/DeepLearningCode/100-Days-Of-ML-Code#hierarchical-clustering--day-54
Visualization.https://cdn-images-1.medium.com/max/800/1*ET8kCcPpr893vNZFs8j4xg.gif
https://github.com/Avik-Jain/100-Days-Of-ML-Code/blob/master/Info-graphs/Day%2054.jpg
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