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Practical Machine Learning

Machine Learning Deep Learning Keras Tensorflow Pytorch Notebooks

Here I will share my notebooks which were made during my Machine Learning Course. These are mainly focused on artificial data generation and the fundamentals of Machine Learning. This is an ongoing blog site and I will be updating this frequently.

Colab
0. Colab Tricks
16.10.2020

Various examples of useful tricks using Google Colab.

Linear Regression
1. Linear Regression
16.1.2020

Various experiments with Linear Regression using custom generated datasets.

Logistic Regression
2. Logistic Regression
26.1.2020

Examples of Logistic Regression on custom datasets.

Poly Lasso
3. Polynomial Regression & LASSO
6.2.2020

Regularization using LASSO to reduce overfitting in polynomial models.

KNN
4. K-Nearest Neighbour
16.2.2020

A taste of clustering algorithms using KNN.

NN
5. Neural Networks using Keras
16.3.2020

Various foundational neural network experiments using Keras.

Transfer Learning
6. CNN Transfer Learning
17.4.2020

First taste of Transfer Learning using Keras models.

Autoencoders
7. Autoencoders & Variants
11.10.2020

Denoising, Reconstructing, and other Autoencoder architectures.

DCGAN
8. DCGAN
06.11.2020

Deep Convolutional GANs on the FASHION MNIST dataset.