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Learn Tensorflow Autoencoders | Best Tutorials and Courses


Taught By: Jose Portilla
Duration: Approx. 14 hours to complete
Description: This course covers the following topics in Machine Learning which we can code using Tensorflow in Python: Installation and Setup of Tensorflow, Introduction to Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, AutoEncoders, Reinforcement Learning, GAN - Generative Adversarial Networks.
Prerequisite: You need to have basic knowledge in Python programming and basic knowledge of maths and statistics.
Taught By: Intellipaat
Duration: Duration
Description: This Tensorflow tutorial helps you to learn the following topics: What are Tensors?, Tensor Rank, Computational Graph, Program Elements in Tensorflow, Constants in Tensorflow, Placeholders in Tensorflow, Variable in Placeholder.
Prerequisite: You need to have basic knowledge of Python programming.
Taught By: Laurence Moroney
Duration: Approx. 30 hours to complete
Description: This course covers the following topics which we can code using TensorFlow in Python: Introduction to Computer Vision, Convolutional Neural Networks.
Prerequisite: This course requires experience in Python coding and intermediate level maths. Also, a brief knowledge about machine learning and deep learning will be helpful, but not required.
Taught By: Aurélien Geron
Duration: Self-Paced
Description: This is one of the best books you can get for someone who is just starting out in Machine Learning, in its libraries such as Tensorflow. The book covers the basics in a very good manner.
Prerequisite: You need to have basic Python knowledge to understand the material in the book.
Taught By: Alex Aklson
Duration: Approx. 8 hours to complete
Description: You will learn about Neural Networks and Deep Learning, Artificial Neural Networks, Building Deep Learning models with Keras, CNN, RNN, Autoencoders, Building a Deep Learning project with Keras.
Prerequisite: You need to know the basics of Machine Learning and Python programming.
Duration: Approx. 2 to 4 hours per week
Description: You will learn about Classification, Training Softmax with PyTorch, Basics of Neural Networks, Deep Neural Networks, Computer Vision Networks (Convolution, Max Pooling, etc.), Dimensionality Reduction, and Autoencoders.
Prerequisite: You need to know the basics of Machine Learning, Deep Learning, and Python programming.
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