Tackle common machine learning problems with Google’s TensorFlow library and build deployable solutions.
- Set up basic and advanced TensorFlow installations
- Deep dive into training, validating, and monitoring training performance
- Set up and run cross-sectional examples using images
- Create pipelines to deal with real-world input data
- Be empowered to go from concept to a production-ready machine learning setup/pipeline capable of real-world usage
You should be familiar with Python and matrix math.
Who is this course intended for?
Packt has been committed to developer learning since 2004. A lot has changed in software since then – but Packt has remained responsive to these changes, continuing to look forward at the trends and tools defining the way we work and live. And how to put them to work.
With an extensive library of content – more than 4000 books and video courses -Packt’s mission is to help developers stay relevant in a rapidly changing world. From new web frameworks and programming languages to cutting-edge data analytics, and DevOps, Packt takes software professionals in every field to what’s important to them now.
From skills that will help you to develop and future-proof your career to immediate solutions to everyday tech challenges, Packt is a go-to resource to make you a better, smarter developer.
|Getting Started with Deep Learning|
|The Course Overview||00:00:00|
|Introducing Deep Learning||00:00:00|
|Installing TensorFlow on Mac OSX||00:00:00|
|Installation on Windows – Pre-Reqeusite Virtual Machine Setup||00:00:00|
|Installation on Windows/Linux||00:00:00|
|Your First Classifier|
|The Hand-Written Letters Dataset||00:00:00|
|Automating Data Preparation||00:00:00|
|Understanding Matrix Conversions||00:00:00|
|The Machine Learning Life Cycle||00:00:00|
|Reviewing Outputs and Results||00:00:00|
|The TensorFlow Toolbox|
|Getting Started with TensorBoard||00:00:00|
|TensorBoard Events and Histograms||00:00:00|
|The Graph Explorer||00:00:00|
|Our Previous Project on TensorBoard||00:00:00|
|Cats and Dogs – Convolutional Neural Networks|
|Fully Connected Neural Networks||00:00:00|
|Convolutional Neural Networks||00:00:00|
|Programming a CNN||00:00:00|
|Using TensorBoard on Our CNN||00:00:00|
|CNN Versus Fully Connected Network Performance||00:00:00|
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