Complete Tensorflow 2 and Keras Deep Learning Bootcamp
What you will learn
What you'll learn
- Learn to use TensorFlow 2.0 for Deep Learning
- Leverage the Keras API to quickly build models that run on Tensorflow 2
- Perform Image Classification with Convolutional Neural Networks
- Use Deep Learning for medical imaging
- Forecast Time Series data with Recurrent Neural Networks
- Use Generative Adversarial Networks (GANs) to generate images
- Use deep learning for style transfer
- Generate text with RNNs and Natural Language Processing
- Serve Tensorflow Models through an API
- Use GPUs for accelerated deep learning
Section 1: Course Overview, Installs, and Setup
Section 2: NumPy Crash Course
Section 3: Pandas Crash Course
Section 4: Visualization Crash Course
Section 5: Machine Learning Concepts Overview
Section 6: Basic Artificial Neural Networks - ANNs
Section 7: Convolutional Neural Networks - CNNs
Section 8: Recurrent Neural Networks - RNNs
Section 9: Natural Language Processing
Section 10: AutoEncoders
Section 11: Generative Adversarial Networks
Section 12: Deployment
Learn to use Python for Deep Learning with Google's latest Tensorflow 2 library and Keras!
- Know how to code in Python
- Some math basics such as derivatives
This course will guide you through how to use Google's latest TensorFlow 2 framework to create artificial neural networks for deep learning! This course aims to give you an easy to understand guide to the complexities of Google's TensorFlow 2 framework in a way that is easy to understand.
We'll focus on understanding the latest updates to TensorFlow and leveraging the Keras API (TensorFlow 2.0's official API) to quickly and easily build models. In this course we will build models to forecast future price homes, classify medical images, predict future sales data, generate complete new text artificially and much more!
This course is designed to balance theory and practical implementation, with complete jupyter notebook guides of code and easy to reference slides and notes. We also have plenty of exercises to test your new skills along the way!
This course covers a variety of topics, including
- NumPy Crash Course
- Pandas Data Analysis Crash Course
- Data Visualization Crash Course
- Neural Network Basics
- TensorFlow Basics
- Keras Syntax Basics
- Artificial Neural Networks
- Densely Connected Networks
- Convolutional Neural Networks
- Recurrent Neural Networks
- GANs - Generative Adversarial Networks
- Deploying TensorFlow into Production
- and much more!
Keras, a user-friendly API standard for machine learning, will be the central high-level API used to build and train models. The Keras API makes it easy to get started with TensorFlow 2. Importantly, Keras provides several model-building APIs (Sequential, Functional, and Subclassing), so you can choose the right level of abstraction for your project. TensorFlow’s implementation contains enhancements including eager execution, for immediate iteration and intuitive debugging, and tf.data, for building scalable input pipelines.
TensorFlow 2 makes it easy to take new ideas from concept to code, and from model to publication. TensorFlow 2.0 incorporates a number of features that enables the definition and training of state of the art models without sacrificing speed or performance
It is used by major companies all over the world, including Airbnb, Ebay, Dropbox, Snapchat, Twitter, Uber, SAP, Qualcomm, IBM, Intel, and of course, Google!
Become a deep learning guru today! We'll see you inside the course!
Who this course is for:
- Python developers interested in learning about TensorFlow 2 for deep learning and artificial intelligence
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