Course Overview
The “TensorFlow for Deep Learning with Python” course is designed to help you gain knowledge of Deep Learning models using TensorFlow. You will learn the architectures of common deep learning models, implement them in TensorFlow 2.0 and learn to optimize them.
Prerequisites
Anyone interested in this program needs to have:
- Basic knowledge of Python, math
- Suggested: Basic understanding of AI, ML
Key Takeaways
- Basics of Deep Learning
- Learn how to build in TensorFlow 2.0:
- Multilayer Perceptron
- Convolutional Neural Network
- Recurrent Neural Network
- Generative adversarial network
- Auto Encoder
- Variational Autoencoder
- Re-enforcement Learning
- Metrics, model tuning, loss functions
- TensorFlow Lite
Target Audience:
- Mathematicians, computer scientists
- Anyone interested in AI, ML and TenorFlow 2.0
Included in this course
- Video Course26 Videos Available
Topic-wise Content Distribution
Recurrent Neural Networks
3 lectures
Reinforcement Learning
2 lectures
Generative Adversarial Networks
2 lectures
Convolutional Neural Network
3 lectures
Tensorflow Features
7 lectures
Working with TensorFlow
8 lectures
Video Lectures
26 Videos Available
Topic-wise Content Distribution
Recurrent Neural Networks
Reinforcement Learning
Generative Adversarial Networks
Convolutional Neural Network
Tensorflow Features
Working with TensorFlow
Why Choose Us?
Online Course
3+ hours of Training Videos for all the objectives. You will be amazed by the way of explaining the concepts that are very easy to understand.
Course validity
Our Courses come with the 2 years of validity.
Experts Support
Our support team consists of Experts, ready to clarify all your questions.
