Machine learning (ML) gives computers the ability to learn without being explicitly programmed. Evolved from the study of pattern recognition and computational learning theory in artificial intelligence, ML explores the study and construction of algorithms that can learn from and make predictions on data through building a model from sample inputs. It’s a really exciting & impactful phase in the ML journey. Today, every time you go to a website, most likely there’s a ML algorithm behind the scenes, analysing the data and interactions, radically heightening your experience using ML
This fast paced hands on worskhop is designed to bootstrap your Deep Learning. It quickly on boards Machine Learning concepts like regression, classification,matrix factorization etc. It introduces algorithms like k Nearest Neighbors, k means, recommender systems etc. It brings in tools like python for quick coding,pandas and numpy for data munging, matplotlib for visualization, scikit-learn for ready made machine learning algorithms. It does so with real life use cases like predicting house sale prices, sentiment analysis using restaurant reviews; real life data like people wikipedia, adult income data etc. and lots of hands on coding. We dive into intuition behind commonly popular algorithm of gradient descent, forward and backward propagation in neural networks. This approach helps imbibe the concepts effectively. We go onto implementing logistic regression as single layer neural network from scratch completely in python. Later we implement generic multi layer neural network in tensorflow.
You can download the entire course content (follow along slides, data for hands on assignments, developed code for all hands on assignments) from github repository. During the course you will develop all the code outlined here from scratch under the guidance of the instructor. I hope that you continue referring to programs developed here for tools, technologies and techniques (3 Ts) even as you progress through your Deep Learning career! Good Luck!
Maths Knowledge Requirements
It would help if you brush up the following topics from high school. Although these are not mandatory, we will cover enough details at the time of workshop.
- Basics of derivatives and concept of maxima-minima.
- Basics of matrix and vector manipulation from linear algebra.