Tensorflow 2.0 is a library created by Google for deep learning and artificial intelligence. With this library, students can learn about all of the major deep learning architectures like Deep Neural Networks, Convolutional Neural Networks, and Recurrent Neural Networks. It is an excellent course for beginner-level students up to expert-level students who want to learn fast.
Course Content
The Tensorflow 2.0: Deep Learning and Artificial Intelligence course has been designed to include a wide range of topics. Students can gain knowledge of machine learning models starting from very basic to advanced concepts. This course is special because it offers hands-on experience for a wide variety of industry-standard neural network-based algorithms, including:
- Computer Vision
- Time Series Analysis
- NLP (Natural Language Processing)
- Gensim
- Reinforcement Learning
- GANs (Generative Adversarial Networks)
Course Rating & Quantity
The Tensorflow 2.0 course has received very high ratings and reviews by the past students. With a course rating aggregate of 4.67007 and 9172 reviews quantity.
The course instructor taught students comprehensively about the concepts of deep learning with practical implementation. The course is very well structured, making it easier for students to understand complex topics in less time. Along with this, the instructor provided hands-on experience with industry-standard algorithms and deep learning architectures.
Course inclusions
Tensorflow is the world's most popular deep learning library, and it makes use of a range of advanced industry concepts. Some of the included projects are time series forecasting, DeepFakes (a potentially nefarious application of deep learning), and the how-to of stock predictions. It offers unique features like explaining each line of code very thoroughly and provides in-depth learning about the approaches that are going to be used in the models.
Course Focus
This course has been designed to build more cool stuff and has less focus on theoretical concepts. It primarily focuses on the breadth of various important deep learning concepts rather than the depth of one particular aspect of deep learning. So, users looking to do in-depth learning can also explore the other dedicated courses of the instructor that focus on individual concepts like recommender systems, natural language processing, reinforcement learning, computer vision, and GANs.
Advanced Tensorflow Topics
The course includes advanced topics such as deploying models with TensorFlow Serving, deploying models with TensorFlow Lite, and writing your own custom TensorFlow model. Students can also learn about converting TensorFlow 1.x code to TensorFlow 2.0, Constants, Variables, and Tensors, Eager execution, and Gradient tape. These advanced TensorFlow topics help students understand and analyze the working of deep learning models to improve them according to the required industry standards.
Why choose Tensorflow 2.0 Course
Apart from the course instructor's excellent teaching style and the course's comprehensiveness, Tensorflow 2.0 is the world's most popular deep learning library. It has evolved into its official second version, making it easier to implement and apply deep learning concepts, such as Generative Adversarial Networks (GANs), Reinforcement Learning, Computer Vision, Time Series Analysis, and Natural Language Processing (NLP).
Towards the end, students will be able to start from a beginner level and build up to expert level concepts. With TensorFlow 2.0, students can learn all the important deep learning concepts and algorithms that are required to build and deploy efficient models.
