Deep Learning with TensorFlow. With the help of this course you can Channel the power of deep learning with Google’s TensorFlow!.
This course was created by Packt Publishing. It was rated 4.7 out of 5 by approx 6944 ratings. There are approx 94250 users enrolled with this course, so don’t wait to download yours now. This course also includes 2 hours on-demand video, 2 Supplemental Resources, Full lifetime access, Access on mobile and TV & Certificate of Completion.
What Will You Learn?
Set up your computing environment and install TensorFlow
Build simple TensorFlow graphs for everyday computations
Apply logistic regression for classification with TensorFlow
Design and train a multilayer neural network with TensorFlow
Understand intuitively convolutional neural networks for image recognition
Bootstrap a neural network from simple to more accurate models
See how to use TensorFlow with other types of networks
Program networks with SciKit-Flow, a high-level interface to TensorFlow
Deep learning is the intersection of statistics, artificial intelligence, and data to build accurate models and TensorFlow is one of the newest and most comprehensive libraries for implementing deep learning. With deep learning going mainstream, making sense of data and getting accurate results using deep networks is possible. This course is your guide to exploring the possibilities with deep learning; it will enable you to understand data like never before. With the efficiency and simplicity of TensorFlow, you will be able to process your data and gain insights that will change how you look at data.
With this video course, you will dig your teeth deeper into the hidden layers of abstraction using raw data. This course will offer you various complex algorithms for deep learning and various examples that use these 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 video course, you will come across topics such as logistic regression, convolutional neural networks, recurrent neural networks, training deep networks, high level interfaces, and more.
With the help of novel practical examples, you will become an ace at advanced multilayer networks, image recognition, and beyond.
About The Author
Dan Van Boxel is a Data Scientist and Machine Learning Engineer with over 10 years of experience. He is most well-known for “Dan Does Data,” a YouTube livestream demonstrating the power and pitfalls of neural networks. He has developed and applied novel statistical models of machine learning to topics such as accounting for truck traffic on highways, travel time outlier detection, and other areas. Dan has also published research and presented findings at the Transportation Research Board and other academic journals.