Amazon Machine Learning Developer Guild Version Latest

Welcome to the Amazon Machine Learning Developer Guide. Amazon Machine Learning (Amazon ML) is a robust, cloud-based service that makes it easy for developers of all skill levels to use machine learning technology. Amazon ML provides visualization tools and wizards that guide you through the process of creating machine learning (ML) models without having to learn complex ML algorithms and technology.

Once your models are ready, Amazon ML makes it easy to obtain predictions for your application using simple APIs, without having to implement custom prediction generation code, or manage any infrastructure. This section introduces the key concepts and terms that will help you understand what you need to do to create powerful machine learning models with Amazon ML.

Note
If you are new to machine learning, we recommend that you read Machine Learning Concepts (p. 8) before you continue. If you are already familiar with machine learning, continue reading this section.

Topics

  • Amazon Machine Learning Key Concepts (p. 1)
  • Accessing Amazon Machine Learning (p. 4)
  • Regions and Endpoints (p. 5)
  • Pricing for Amazon ML (p. 5)

Related posts:

Python Data Analytics with Pandas, NumPy and Matplotlib - Fabio Nelli
Hands-on Machine Learning with Scikit-Learn, Keras & TensorFlow - Aurelien Geron
Statistical Methods for Machine Learning - Disconver how to Transform data into Knowledge with Pytho...
Applied Text Analysis with Python - Benjamin Benfort & Rebecca Bibro & Tony Ojeda
Introducing Data Science - Davy Cielen & Arno D.B.Meysman & Mohamed Ali
Deep Learning with PyTorch - Vishnu Subramanian
Python Machine Learning Cookbook - Practical solutions from preprocessing to Deep Learning - Chris A...
R Deep Learning Essentials - Dr. Joshua F.Wiley
Introduction to Deep Learning Business Application for Developers - Armando Vieira & Bernardete Ribe...
Python Deep Learning - Valentino Zocca & Gianmario Spacagna & Daniel Slater & Peter Roelants
Deep Learning with Python - Francois Cholletf
Python Deep Learning Cookbook - Indra den Bakker
Deep Learning - Ian Goodfellow & Yoshua Bengio & Aaron Courville
Artificial Intelligence - A Very Short Introduction - Margaret A.Boden
Introduction to Machine Learning with Python - Andreas C.Muller & Sarah Guido
Learning scikit-learn Machine Learning in Python - Raul Garreta & Guillermo Moncecchi
Building Chatbots with Python Using Natural Language Processing and Machine Learning - Sumit Raj
Python Machine Learning Eqution Reference - Sebastian Raschka
Python for Programmers with introductory AI case studies - Paul Deitel & Harvey Deitel
Natural Language Processing with Python - Steven Bird & Ewan Klein & Edward Loper
Understanding Machine Learning from theory to algorithms - Shai Shalev-Shwartz & Shai Ben-David
Practical computer vision applications using Deep Learning with CNNs - Ahmed Fawzy Gad
Deep Learning with Python - Francois Chollet
Python Machine Learning - Sebastian Raschka
Python Data Structures and Algorithms - Benjamin Baka
Introduction to Deep Learning - Eugene Charniak
Neural Networks and Deep Learning - Charu C.Aggarwal
Python Deeper Insights into Machine Learning - Sebastian Raschka & David Julian & John Hearty
Artificial Intelligence - 101 things you must know today about our future - Lasse Rouhiainen
Natural Language Processing Recipes - Akshay Kulkni & Adarsha Shivananda
Deep Learning for Natural Language Processing - Palash Goyal & Sumit Pandey & Karan Jain
Foundations of Machine Learning second edition - Mehryar Mohri & Afshin Rostamizadeh & Ameet Talwalk...