Advance Your Skills in Deep Learning and Neural Networks
The hottest new frontier in the universe of AI and machine learning is in deep learning and neural networks. This learning path is your entryway into the tools, concepts, and finer points of computer vision, natural language processing, and more.
Master the basics of computer vision.
Explore the applications of building neural networks.
Learn how natural language processing (NLP) works.
Building Deep Learning Applications with Keras 2.0 with Adam Geitgey
Learn how to install Keras— a popular deep learning framework—and use it to build a simple deep learning model.
1h 24m • COURSE
Deep Learning: Face Recognition with Adam Geitgey
Learn how to develop a face recognition system by leveraging deep learning. Find out how to code for face detection, identification, and more.
1h 25m • COURSE
Deep Learning: Image Recognition with Adam Geitgey
Learn how to design, build, and deploy a deep neural network to serve as an image recognition system.
1h 43m • COURSE
Building and Deploying Deep Learning Applications with TensorFlow with Adam Geitgey
Discover how to install TensorFlow and use it to create, train, and deploy a machine learning model.
1h 46m • COURSE
Neural Networks and Convolutional Neural Networks Essential Training with Jonathan Fernandes
Take a deep dive into neural networks and convolutional neural networks, two key concepts in the area of machine learning.
1h 19m • COURSE
57m • COURSE
Accelerating TensorFlow with the Google Machine Learning Engine with Matt Scarpino
Learn how to use TensorFlow to build high-performing machine learning apps. Discover how to develop and run applications on the Google Cloud Machine Learning Engine.
3h 5m • COURSE
Introduction to AWS DeepLens with Jonathan Fernandes
Get started with AWS DeepLens, the world's first deep learning-enabled video camera for developers.
33m 50s • COURSE
NLP with Python for Machine Learning Essential Training with Derek Jedamski
Explore natural language processing (NLP) concepts, review advanced data cleaning and vectorization techniques, and learn how to build machine learning classifiers.
4h 14m • COURSE
You'll learn deep learning and neural network skills with these experts.
Adam Geitgey is a developer who is captivated by how machine learning is changing software development.
His background is in building large-scale websites and helping startups in Silicon Valley take advantage of machine learning. He has a passion for putting theory into practice—taking cutting-edge developments in machine learning and sharing them with software developers of all skill levels.
Jonathan Fernandes works for a consultancy and primarily focuses on data science, AI, and big data.Jonathan enjoys his work, as it combines his love of numbers, coding, and statistics. Jonathan has an undergraduate degree in computer science, and an MBA from the University of Warwick.
Emmanuel Henri is a full-stack developer with 20 years of experience in programming, technology, and design.
Matthew Scarpino is a deeply experienced software developer specializing in high-speed software development.Currently, Matthew works as a software developer at Plutocracy.com, a company that aims to harness the power of deep learning to support individual investors and small investing firms. In his current role, he implements stock forecasting using Python, spline interpolation, and recurrent neural networks (RNNs). He has deployed TensorFlow models to the Google Cloud Machine Learning Engine for high-speed processing. Matthew's specialties include C++, Python, TensorFlow, and the Google Cloud Platform (GCP).
Derek Jedamski is a skilled data scientist specializing in machine learning.
Derek has experience with regression and classification modeling, natural language processing, statistical analysis, quality control, business analytics, and communicating technical results to audiences with various backgrounds. He also has a thorough understanding of Python, R, SQL, Apache Spark, and other computing frameworks and languages. Currently, Derek works at GitHub as a data scientist.
Learning Paths are big commitments. Keep your goal in focus by taking one at a time. Starting Advance Your Skills in Deep Learning and Neural Networks will pause your previous path and save your progress.