Day 1:Regression in TF : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/06-Regression-Exercise-SA-Udemy-TF.ipynb
Day 2:Classification in TF : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/08-Classification-Exercise-SA-udemy-TF.ipynb
Day 3:MNIST Data classification TF : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/00-MNIST-Data-Basic-Approach-SA-Udemy-TF.ipynb
Day 4:Fourier Applications : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/Fourier_apps-Udemy-SA.ipynb
Day 5:Credit scoring & MNIST with CNN Part-1 : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/01-MNIST-with-CNN-part1-udemy-TF.ipynb
Day 6:Basic SKLearn Revision : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/SK-Learn-Overview-Udemy-Git.ipynb
Day 7:MNIST with CNN Final : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/01-MNIST-with-CNN-Final-Udemy_GIT-SA.ipynb
Day 8:CIFAR-10 CNN : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/02-CNN-Project-Exercise-udemy-git-SA-CIFAR-10.ipynb
Day 9:OpenCV Image Sketch : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/custom_blur_udemy-conv-git-sa.py
Day 10:Timeseries using RNN : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/Basic-Manual-RNN-SA-Udemy-Git.ipynb
Day 11:Deep Nets with TF Abstractions : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/Deep-Nets-with-TF-Abstractions-udemy-git-sa.ipynb
Day 12:Deep Net with Keras : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/Deep-Nets-with-Keras-udemy-git-SA.ipynb
Day 13:Simple Autoencoder without activation : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/Simple-Autoencoder-for-PCA-Udemy-Git-SA.ipynb
Day 14:Stacked Autoencoders : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/Stacked-Autoencoder-udemy-git-sa.ipynb
Day 15:GANs : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/GAN-basic.ipynb
Day 16:Conv Edge : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/edge-udemy-git-sa.py
Day 17:Conv Edge benchmark : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/edge_benchmark-udemy-sa-git.py
Day 18:MNIST various method 1 : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/MNIST%20CNN%20Various%20methods.ipynb
Day 19:MNIST various method 2 : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/MNIST%20CNN%20Various%20methods%202.ipynb
Day 20:NN Manual 1 : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/NN%20manual%201.ipynb
Day 21:NN Manual 2 : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/NN%20manual%202.ipynb
Day 22:Linear Regression - back to basics : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/Linear%20Regression%20-%20back%20to%20basics.ipynb
Day 23:Logistic Regression from Scratch 1 : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/Logistic%20Regression%20from%20Scratch%201.ipynb
Day 24:Prophet : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/Prophet%20Python.ipynb
Day 25:ARIMA : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/ARIMA.ipynb
Day 26:Linear Regression 101
Day 27:MV Linear Regression 101
Day 28:Gradient Descent LR
Day 29:L1 LR
Day 30:L2 LR
Day 31:Logistic Regression 101
Day 32:Logistic Regression GD
Day 33:Imputation Part 1
Day 34:Logistic regression L2
Day 35:Logistic regression L1
Day 36:
Day 37:Survival Analysis part 1
Day 38:Survival Analysis part 2
Day 39:LR Facial Expression Recognition
Day 40:Network Analysis Airport Data
Day 41:KM Clustering
Day 42:Bias Variance
Day 43:Feed Forward
Day 44:Word Cloud 101
Day 45:Back Prop
Day 46:Airline Time series by regression
Day 47:Isotonic Regression : https://github.com/srayagarwal/100daysMLcodingChallenge/blob/master/isotonic%20regression.ipynb
Day 48:silhouette_score : 100daysMLcodingChallenge/silhouette_score.ipynb
Day 49:Copula
Day 50:Feature Selection