What’s popular in machine learning
Your source for what’s next
Popular in live online training
See allJuly 7, 2022
Getting Started with Tensorflow.js
Presented by Brian Sletten
Machine learning in the browser Machine learning (ML) helps manage the explosion of data that we no longer have the capacity to approach with conventional strategies. TensorFlow.js leverages the availability of ...
May 31, 2022
Introduction to Machine Learning in Cybersecurity
Presented by Dr. Chuck Easttom
This is an overview of how machine learning impacts cybersecurity. The first 60% of the course is an introduction to machine learning covering a wide range of techniques and algorithms. Then ...
June 22, 2022
Graph-Powered Machine Learning First Steps
Presented by Jörg Schad
From graph analytics to graph neural networks: Making the most of your graph data Many powerful machine learning algorithmsâincluding PageRank (Pregel), recommendation engines (collaborative filtering), and text summarization and other NLP ...
June 22, 2022
Docker for Machine Learning Engineers—with Interactivity
Presented by Jonathan Fernandes
One of the challenges when working in machine learning is the continuous stream of new libraries that are available and standardising the development environment for the team. Docker allows us to ...
June 27, 2022
Explainable Machine Learning Models—with Interactivity
Presented by Parul Pandey
Making sense of opaque and complex models using Python Machine Learning is a powerful tool and is being increasingly used in multi-faceted ways across several industries. These AI models are being ...
May 23, 2022
Automated Machine Learning with Microsoft Azure
Presented by Axel Sirota
Get the best model for your data Building machine learning models means constantly iterating on the best features, the best architectures, and the best algorithms until you get a model that ...
Popular in interactive learning
See allPython ML Cookbook: Wrangling Data (Part 2)
By O'Reilly Media, Inc.
Recipes from Machine Learning with Python Cookbook ...
Handling Categorical Data: Handling Imbalanced Classes
By Vishwesh Ravi Shrimali
Handling imbalanced classes in Scikit-Learn using upsampling and downsampling ...
Regularization in Regression Using Python
By Siddharth Yadav
In this scenario, you will learn how to use regularization in linear regression models effectively ...
Deploy MLflow
By Chris Fregly
Learn how to deploy MLflow ...
Handling Categorical Data: Imputing Missing Class Values
By Vishwesh Ravi Shrimali
Imputing missing class values using mode and k-NN model ...
Machine Learning Challenge: Find Topics Using GloVe and PCA
By Matt Kirk
Using GloVe vectorization and PCA, you will find topic clusters of terms ...
Articles on Radar
See allMachine Learning and the Production Gap
By Mike Loukides
The biggest problem facing machine learning today is getting machine learning from the researcher’s laptop to production.
Moving AI and ML from research into production
By Jenn Webb
Dean Wampler discusses the challenges and opportunities businesses face when moving AI from discussions to production.
