3784f2c199f2fa723d07f87ba413cc8b

Abstract

-Introduction
-Python basic of machine learning libraries
-What is Machine Learning? Differences between Machine learning/Deep Learning/Neural Networks/AI
-Types of ML: Supervised, unsupervised
-What are the features? Getting an idea for Feature Extraction.
-Linear regression
cost function
gradient descent
-Locally Weighted regression
-logistic regression
-Softmax regression
-Naïve Bayes hands-on Digit Recognizing with MNIS
-classification
images(Dog and Cat)
-Neural Network, Types of NN, The Perceptron
Writing first NN using Python

Speaker

Tanisha Bhayani

Timing

Starts at Saturday August 17 2019, 11:15 AM. The sessions runs for about 7 hours.

Resources