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An Overview of Machine Learning in the Wolfram Language
Video Lesson | FREE

This video gives an overview of the highly automated machine learning framework in the Wolfram Language, which allows you to do so much with just a few lines of code. You will learn about high-level functions that are task oriented and can be applied to a variety of input such as text, images and numeric data. Examples include building a simple image search and classification system, topic classification of text and prediction of sale prices of homes.

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Building Blocks for Deep Learning
Video Course | FREE

This video course explores how to construct neural networks in the Wolfram Language. The Wolfram Language neural network framework provides symbolic building blocks to build, train and tune a network, as well as automatically process input and output using encoders and decoders. You'll learn how to build feed-forward networks and about recurrent neural nets and why they are interesting.

Course Overview
  • Video 128 minutes
  • Video 227 minutes
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Introduction to Image Processing
Interactive Course | FREE

Requirements: This course requires basic working knowledge of the Wolfram Language.

Certification Levels: CompletionLevel 1

Make cutting-edge image processing simple with the Wolfram Language. Learn the fundamentals of digital image processing, including image representation and classical operations on images. This course emphasizes practical applications and understandable explanations of how image operations work. Numerous examples are included to illustrate standard applications.

Course Overview
  • Section 138 minutes
  • Section 241 minutes
  • Section 336 minutes
  • Section 426 minutes
  • Section 536 minutes
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Learning to Tackle Real-World Computer Vision Applications
Video Lesson | FREE

How can you apply the deep learning framework integrated in the Wolfram Language for solving real-world image processing applications? This class explores some of the depth of the Wolfram Language's neural net framework capabilities and shows how the trained networks can be tweaked to suit a wide range of complex image analysis tasks. With the help of examples, you will gain practical insights into effectively leveraging neural nets for your own applications.

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Multiparadigm Data Science
Interactive Course | FREE

Requirements: This course requires basic working knowledge of the Wolfram Language

Certification Levels: CompletionLevel 1Level 2

Multiparadigm Data Science is a rapidly advancing new approach of using modern analytical techniques, automated machine learning and human-data interfaces to arrive at better answers. This course introduces the basic concepts of the multiparadigm approach, demonstrating both the flexible, integrated project workflow and the broad computational toolkit that supports it from start to finish. Discover best practices, exploration techniques and ways to leverage the high-level Wolfram Language to get real, quantifiable answers to the full range of data science problems.

Course Overview
  • Section 132 minutes
  • Section 225 minutes
  • Section 316 minutes
  • Section 458 minutes
  • Section 524 minutes
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The Wolfram Language: Introduction to Machine Learning
Instructor Led | See Course Page for Price

Requirements: This course requires basic working knowledge of the Wolfram Language.

Certification Levels: Completion

This course introduces the easy-to-use machine learning superfunctions available in the Wolfram Language. You will learn how to perform supervised and unsupervised learning tasks with just a few lines of code. We will start with regression, classification, clustering and anomaly detection, and from there, we'll move on to the state-of-the-art Neural Net Framework. Examples using the Wolfram Neural Net Repository are shown with instructions for building your own neural networks from scratch. Basic familiarity with the Wolfram Language or introductory-level skill in any programming language is recommended.

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Video Creation, Editing and Analysis Using the Wolfram Language
Video Course | FREE

Learn how to create, edit, process and analyze videos with the Wolfram Language. You can capture videos using webcams, or create them using files, images, existing video clips or built-in functions that create individual frames. Then learn how to cut, alter and compose video footage with dedicated functions for video editing and processing. You can also learn how to enhance video quality, perform color correction and combine videos and images using overlays and grids. This course includes examples of applying machine learning and neural networks to process videos and recognize objects, faces, speech or actions in the videos.

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Wolfram Technology in Action: Data Science Webinar Series
Archived Special Event | FREE

This three-part webinar series showcases a range of data science applications in the Wolfram Language, featuring talks from the 2019 Wolfram Technology Conference. Presentations highlight built-in Wolfram Language functionality for data analysis, modeling, visualization, automated reporting and machine learning. Topic areas include Twitter analytics, tidal flooding, computational taxonomy, video game AI planning and more.

Course Overview
  • Video 177 minutes
  • Video 281 minutes
  • Video 375 minutes
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Zero to AI in 60 Minutes
Video Course | FREE

Follow this video series to get started with machine learning in the Wolfram Language. Automated machine learning capabilities in the Wolfram Language and machine learning concepts are demonstrated with the use of examples. Start with the concept of supervised learning and three key techniques: classification, prediction and sequence prediction. Learn how to work with various types of data, select from predefined methods and interpret results. Common issues related to datasets and ways to address them are discussed. Move on to the concept of unsupervised machine learning tasks such as feature extraction, encoding and dimension reduction. Text and image classification examples are used to demonstrate these methods. Next, get an overview of the neural network framework integrated in the Wolfram Language. Finally, learn how to deploy developed models through APIs and web forms for use by external programs and individuals.

Course Overview
  • Video 13 minutes
  • Video 221 minutes
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  • Video 56 minutes
  • Video 616 minutes
  • Video 77 minutes
  • Video 86 minutes
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An Overview of Deep Neural Networks Applications

An Overview of Deep Neural Networks Applications
Video Lesson | FREE

A high-level overview of deep neural networks applications. This class shows many examples of problems that can be solved with deep neural nets, including image classification, sequence prediction, speech recognition and question answering. The class concludes with a case study of how the ImageIdentify function was built on the Wolfram neural network framework. This class assumes some familiarity with the Wolfram Language and neural network concepts.

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Analyzing Text to Answer Fact-Based Questions

Analyzing Text to Answer Fact-Based Questions
Video Lesson | FREE

This video class introduces FindTextualAnswer, the built-in Wolfram Language function that combines well-established techniques for information retrieval with state-of-the-art deep learning techniques to find answers in text. FindTextualAnswer analyzes text and can yield several possible answers, the probabilities of those answers being correct and other properties that can help you understand the context of each answer in response to your specific, fact-based questions. In this class, you will learn the scope of this function and some practical applications, as well as gain insights into how it is implemented and the deep learning approach available in the Wolfram Language.

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Applying Neural Networks Webinar Series

Applying Neural Networks Webinar Series
Archived Special Event | FREE

This webinar series takes you on a deep dive into the latest workflows for building, training and evaluating neural networks. See how neural net models are used to solve complex processing tasks involving image, audio and natural language data. Sessions include hands-on demonstrations, showing real-world applications using the latest built-in Wolfram Language functionality and neural net models. Pretrained models from the Neural Net Repository and customized models are shown.

Course Overview
  • Video 16 minutes
  • Video 245 minutes
  • Video 322 minutes
  • Video 46 minutes
  • Video 517 minutes
  • Video 642 minutes
  • Video 711 minutes
  • Video 88 minutes
  • Video 957 minutes
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Automated Data Science

Automated Data Science
Video Course | FREE

Learn about machine learning functions that have been tuned to automate the data science process. This video course shows examples of using computation with data that go beyond traditional statistical methods and highlight the role of automated modeling in the modern data science process. Automated classification and regression functionalities are demonstrated using the built-in Wolfram Language symbols Classify and Predict.

Course Overview
  • Video 135 minutes
  • Video 225 minutes
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Automated Structure Discovery: Unsupervised Learning

Automated Structure Discovery: Unsupervised Learning
Video Lesson | FREE

The Wolfram Language has functions that work directly on many types of data and automatically extract some sort of structure from it. FindClusters, ClusteringTree and ClusteringComponents are examples of functions that perform the unsupervised learning task of clustering. ClusterClassify classifies new samples based on information gathered from unlabeled input data via clustering. Other functions like FeatureExtract, FeatureNearest, FeatureSpacePlot and DimensionReduce provide tools for automatic exploration of the data in the feature space. This video introduces these functions to get you started on unsupervised machine learning tasks. It is suitable for beginners without previous knowledge of machine learning.

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Building and Training Basic Neural Networks

Building and Training Basic Neural Networks
Video Lesson | FREE

The Wolfram Language neural network framework provides symbolic building blocks to build, train and tune a network as well as automatically process input and output using encoders and decoders. Learn how to do this in steps, along with examples of logistic regression and basic image recognition.

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Building Applications with the Wolfram Neural Net Repository

Building Applications with the Wolfram Neural Net Repository
Video Lesson | FREE

Learn to build applications using the neural network models available in the Wolfram Neural Net Repository. This class showcases existing models in the repository and the different tasks for which they are intended, such as classification, feature extraction, image processing, regression, language modeling and more, with new models and new application areas being added all the time. Use cases showing applications built by students from Wolfram summer programs are shared. Learn to leverage available models to create your own applications.

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