Machine Learning and Deep Learning Using TensorFlow

Artificial Intelligence (AI): Machine Learning, Deep Neural Networks (DNN), and Convolution Neural Networks (CNN)

Created by: Saikat Ghosh
AI Entrepreneur

What Will I Learn?

• In depth understanding of Machine Learning.
• In depth understanding of the Neural Network.
• Detailed and step by step theoretical derivation and explanation of a majority of the topics to ensure clear understanding of the subject.
• You will learn Linear Regression, Logistic Regression, Neural Network, Deep Neural Network (DNN), Convolution Neural Network etc.
• Multiple hands-on projects using Tensorflow 2 and Python to expose you to some of the highly advanced topics of Tensorflow 2
• Hands-on projects are selected to make you familiar with some of the expertise that may be very useful should you need to run a very long analysis in future.

Requirements

• For Theory Section: Some knowledge in algebra and calculus.
• For Hands-On Section: Gmail account to use Google Colab and Google Drive. Basic programming knowledge using Python 3
• If you have no programming background, you may still take the course. You can still benefit from the mathematical understanding of the subject. You can play with all the code that is provided.
• All codes are provided for you to download.
• No software needed to install on your computer. We will use Google Colab with step-by-step set up instructions included in the course.

Target audience

• Who is this course for? Almost for everyone. Machine Learning is not a topic for one single profession. Machine Learning (along with neural networks) is an immensely powerful tool that may help you to find solutions to some of the problems that one may not know how to solve otherwise. Try this course and see if it gives you better insight to address some of the problems you are working on.
• People from a diverse range of professions may find this knowledge useful in their own profession.
• Topics are explained in detail. Concepts are developed progressively in a step by step manner. I sometimes spent more than 10 minutes discussing a single slide instead of rushing through it. This should help you to be in sync with the material presented and help you better understand it.
• The hands-on examples are selected primarily to make you familiar with some aspects of TensorFlow 2 or other skills that may be very useful if you need to run a large and complex neural network job of your own in the future.
• Please watch the first two videos to have a better understanding of the course.