Deep Learning : Plunge into Deep Learning

Interested in the field of Machine Learning and Deep Learning? Then this course is for you!

This course is designed in a very simple and easily understandable content.

You might have seen lots of  buzz on deep learning and you want to figure out where to start and explore.

This course is designed exactly for people like you!

If basics are strong, we can do bigger things with ease.

My focus in this course is to build complicated things starting from very basics

In this course, I will cover the following things

• Session 1 – Introductory material on Deep learning, its applications and significance.

• Session 2 -  Introduces the fundamental building block of deep learning

• Session 3 – Logistic Regression, Activation Functions, Perceptron, One Hot Encoding, XOR problem and Multi-Layer Perceptron models

• Session 4 – Training of Neural Networks: Cross Entropy, Loss Function, Gradient descent Algorithm, Non-Linear Models, Feed Forward, Backward propagation, Overfitting problem, Early stopping, Regularization, drop out and Vanishing Gradient problem.

• Session 5 – Convolution Neural Networks:  Feature Extraction, Convolution Layer, Pooling Layer, Relu, Flattening and Deep Convolution Neural Networks.

• Session 6 – Sequence Models: Recurrent Neural Networks, LSTMs

Are there any course requirements or prerequisites?

• Just some high school mathematics level.

Who this course is for:

• Anyone interested in Machine Learning and Deep Learning

• Students who have high school knowledge in mathematics and who want to start learning Deep Learning

• Any intermediate level people who know the basics of machine learning, who want to learn more advanced topics like deep learning

• Any students in college who want to start a career in Data Science

• Any data analysts who want to level up in Machine Learning and Deep Learning

• Any people who are not satisfied with their job and who want to become a Data Scientist

• Any people who want to create added value to their business by using powerful Learning tools

• Build a foundation on the principles of Deep Learning to understand the latest trends