Machine Learning and Deep Learning - Four Weekends

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Machine Learning and Deep Learning - Four Weekends


Why Should I Learn Machine Learning & Deep Learning?

If you want to break into cutting-edge AI, this course will help you do so. Machine learning and Deep learning engineers are highly sought after, and mastering deep learning will give you numerous new career opportunities. Machine learning and Deep Learning is also a new "superpower" that will let you build AI systems that just weren't possible a few years ago.

This is a Four Week Course (not including the first free week).

Week 0 : Python for Data Science (a Free Course, prepares you for this course).

Week 1 : Introduction to Machine Learning This course introduces to the joy of machine learning.

  • Machine Learning Concepts

    • MLA’s Seven Step Supervised Learning Process

    • Data Abstraction

    • Feature Engineering

    • Train Test Splitting

    • Model Evaluations

  • Algorithms covered:

    • Logistic Regression

    • Linear Regression

    • Text / Sentiment Analysis

    • K - Means

Week 2 : Advanced Machine Learning. This week you will learn the math and the programming and some more algorithms

  • Machine Learning Concepts

    • Model Tuning

    • Feature Selections

    • Regularization

    • Overfitting / Underfitting

  • Algorithms covered:

    • XG-Boost

    • Time Series Analysis

    • K - Nearest Neighbours

    • and many more

Week 3 : Basic Deep Learning

Neural Networks has shown its power in Image Recognition, Character Recognition, Forecasting and many other areas where predictions can be made with a much higher accuracy than others. So the next four sessions aim at delving you deeper into the world of Deep Learning. You will know about Artificial Neural Networks (ANN) and Convolution Neural Networks (CNN) and have hands-on experience in building an ANN and CNN.

  • Session 1: Introduction to Artificial Neural Networks (ANN)

  • Session 2: Building of Artificial Neural Networks (ANN)

  • Session 3: Introduction to Convolution Neural Networks (CNN)

  • Session 4: Building of Convolution Neural Networks (CNN)

Week 3 : Advanced Deep Learning

After learning ANN and CNNs it is time to move on to advanced Neural Networks concepts. We go into Recurrent Neural Networks.

  • Session 1: Introduction to Recurrent neural network and LSTM

  • Session 2: Project in LSTM

  • Session 3: Autoencoders - Unsupervised Deep Learning

  • Session 4: GANs - Generate images

Who Can Attend?
People who have attended the Basics - Machine Learning 101 or has prior knowledge of Machine Learning (Python is preferred, but any programming background is fine).

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