shyamsunder007 / 100daysofml

100 Days of ML Challenge

Day 1 : July 5, 2018

• Today's Progress: I picked up the Boston House Pricing dataset for implementing Linear Regression.
• Thoughts: I chose this dataset just as a warmup.
• Link to the code

Day 2 : July 6, 2018

• Today's Progress: After learning the basics of Keras, I implemented Sequential model on Breast Cancer Dataset available in scikit-learn.
• Thoughts: I am currently enrolled in a course, so this Keras lecture is a part of the course.
• Link to the code

Day 3 : July 7, 2018

• Today's Progress: I built a Convolutional Neural Network in Tensorflow to classify the images in MNIST dataset. This dataset has images of handwritten digits. The model runs at an accuracy of 98%.
• Link to the code

Day 4 : July 8, 2018

• Today's Progress: Improved the code done yesterday by building a Convolutional Neural Network in Keras to classify the images in MNIST dataset. The accuracy of the model is 99.4%.
• Link to the code

Day 5 : July 9, 2018

• Today's Progress: I used the Cifar10 dataset on the Convolutional Neural Network built using Keras. Cifar10 dataset has images which belong to one of the 10 classes like bird, truck, cat, frog, etc.
• Link to the code

Day 6 : July 10, 2018

• Today's Progress: I learnt RNN, which is a part of the course. So, I built a network containing SimpleRNN layer, in order to understand the whole working. The dataset used is International-Airline-Passengers.
• Link to the code

Day 7 : July 11, 2018

• Today's Progress: I implemented Naive Bayes classifier from scratch, and used it for predicting the classes in Iris Dataset available in Scikit-learn.
• Link to the code