Channel the power of deep learning with Google's TensorFlow!
About This Deep Learning with TensorFlow Video course
- Explore various possibilities with deep learning and gain amazing insights from data using Google’s brainchild—TensorFlow
- Want to learn what more can be done with deep learning? Explore various neural networks with the help of this comprehensive guide!
- Rich in concepts, this is an advanced guide on deep learning that will give you the background to innovate in your environment
Deep Learning with TensorFlow In Detail
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 video 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 tutorial, 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.
Tensorflow, Data Science training table of contents (duration : 2h30s)
- The Course Overview free 00:03:00
- Installing TensorFlow free 00:05:34
- Simple Computations 00:05:32
- Logistic Regression Model Building 00:06:59
- Logistic Regression Training 00:04:53
Deep Neural Networks
- Basic Neural Nets 00:05:17
- Single Hidden Layer Model 00:05:06
- Single Hidden Layer Explained 00:04:33
- Multiple Hidden Layer Model 00:05:22
- Multiple Hidden Layer Results 00:04:43
Convolutional Neural Networks
- Convolutional Layer Motivation 00:05:04
- Convolutional Layer Application 00:06:56
- Pooling Layer Motivation 00:03:59
- Pooling Layer Application 00:04:18
- Deep CNN 00:06:29
- Deeper CNN 00:04:08
- Wrapping Up Deep CNN 00:04:56
Recurrent Neural Networks
- Introducing Recurrent Neural Networks free 00:09:03
- Skflow 00:09:19
- RNNs in skflow 00:04:04
- Research Evaluation 00:06:56
- The Future of TensorFlow 00:04:19