Video Tutorials →Machine Learning Projects with TensorFlow 2.0
Video: .MP4, AVC, 1920x1080, 30 fps | Audio: English, AAC, 44.1 KHz, 2 Ch | Duration: 4h 20m | 956 MB
Instructor: Vlad Sebastian Ionescu
Build and train models for real-world machine learning projects using Tensorflow 2.
Strengthen your foundations to build TensorFlow 2.0 projects by exploring its new features
Analyze the Titanic data set to obtain desired results with ease
Implement and organize your Tensorflow projects in a professional manner
Use Tensorboard to inspect various metrics and monitor your project's performance
Research and make the most of other people's Kaggle solutions
Use OpenAI Gym Environments for implementing state of the art reinforcement learning techniques using TF-Agents
Apply the latest Transfer Learning techniques from Tensorflow
TensorFlow is the world's most widely adopted framework for Machine Learning and Deep Learning. TensorFlow 2.0 is a major milestone due to its inclusion of some major changes making TensorFlow easier to learn and use such as "Eager Execution". It will support more platforms and languages, improved compatibility and remove deprecated APIs.
This course will guide you to upgrade your skills in Machine Learning by practically applying them by building real-world Machine Learning projects.
Each section should cover a specific project on a Machine Learning task and you will learn how to implement it into your system using TensorFlow 2. You will implement various Machine Learning techniques and algorithms using the TensorFlow 2 library. Each project will put your skills to test, help you understand and overcome the challenges you can face in a real-world scenario and provide some tips and tricks to help you become more efficient. Throughout the course, you will cover the new features of TensorFlow 2 such as Eager Execution. You will cover at least 3-4 projects. You will also cover some tasks such as Reinforcement Learning and Transfer Learning.
By the end of the course, you will be confident to build your own Machine Learning Systems with TensorFlow 2 and will be able to add this valuable skill to your CV.
Codefiles are uploaded here:
Make use of the amazing new feature of TensorFlow 2 called 'Eager Execution' which makes it easier to learn and use
Upgrade your skills by building real-world Machine Learning projects
Build, test and deploy different ML models and learn more modern techniques such as Reinforcement Learning and Transfer Learning
- Coursera - TensorFlow in Practice Specialization by deeplearning.ai
- A Practical Guide to Machine Learning with TensorFlow 2.0 & Keras
- Build, Train, and Deploy Your First Neural Network with TensorFlow
- Addison Wesley Professional Deep Learning with TensorFlow Keras and PyTorch Sneak Peak
- End-to-End Machine Learning with TensorFlow on GCP