Channel the power of deep learning with Google’s TensorFlow!
Beginner Level, – 2 hours, 22 lectures
Average rating 4.0/5 (4.0 (43 ratings) Instead of using a simple lifetime average, Udemy calculates a course’s star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.)
Some familiarity with C++ or Python is assumed.
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.
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
If you are a data scientist who performs machine learning on a regular basis, are familiar with deep neural networks, and now want to gain expertise working with convoluted neural networks, then this course is for you.
“Most of the course is listening to someone commenting on code while copy-pasting examples from a vim window to ipython (everything in the console). Because of this, don’t expect diagrams or any visual help during the course, you won’t even see a mouse cursor pointing at the code that is being explained. If you’re a visual learner, avoid this unless you want to end up reading code and doing the diagrams yourself with a pen and paper.
A lot of basics things are explained while complex things are left out.
I ended up reading the official documentation for the functions used, just to find out *some* of them were explained in later lectures.
It feels rushed, even though the code is actually pretty simple.
I can’t tell if the instructor is an expert on the topic, but you can definitely find better content on youtube, just search for Deep Learning with Tensorflow.
If you don’t care for the certificate, it’s definitely not worth the money.” (Manuel Levi)
“Was a very good introduction to both TensorFlow and deep neural networks. I am confident I can apply this knowledge right away to my own machine learning projects!” (Eric Romero)
“This course if good for me. I know python and I know machine learning. I want to learn the TF model from the top to the bottom.” (Raoul-emil Khouri)
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