Introduction to Deep Learning with TensorFlow
New – Learn advanced machine learning and neural networks with Python in this self-paced course.
GK# 7723
New – Learn advanced machine learning and neural networks with Python in this self-paced course.
GK# 7723
This course is your guide to explore possibilities with deep learning—it will enable you to understand data like never before. You will be able to process your data and gain insights which would change how you look at data. You will dig your teeth deeper into the hidden layers of abstraction using raw data. It teaches various complex algorithms for deep learning with examples that use different deep neural networks. You will also learn how to train your machine to craft new features to make sense of deeper layers of data. During the course, you will come across topics like logistic regression, convolutional neural networks, advanced multilayer perceptrons and how to implement them using real-world datasets.
Introduction to Deep Neural Networks
First Look at TensorFlow
TensorFlow on a Convolutional Neural Network
Implementing a Restricted Boltzmann Machine with TensorFlow
Optimizing TensorFlow using an Autoencoder
Sentiment analysis with TensorFlow and LSTMs
Data scientists and machine learning engineers who wish to dive deep into the fundamentals of deep learning will find this course to be very useful. Some experience with Python programming will be required, while understanding of some fundamental calculus and linear algebra will also help.
This course is available in the following formats:
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