- AutoML: An Introduction Using Auto-Sklearn and Auto-PyTorch - Oct 11, 2021.
AutoML is a broad category of techniques and tools for applying automated search to your automated search and learning to your learning. In addition to Auto-Sklearn, the Freiburg-Hannover AutoML group has also developed an Auto-PyTorch library. We’ll use both of these as our entry point into AutoML in the following simple tutorial.
Automated Machine Learning, AutoML, Python, PyTorch, scikit-learn
- KDnuggets™ News 21:n36, Sep 22: The Machine & Deep Learning Compendium Open Book; Easy SQL in Native Python - Sep 22, 2021.
The Machine & Deep Learning Compendium Open Book; Easy SQL in Native Python; Introduction to Automated Machine Learning; How to be a Data Scientist without a STEM degree; What Is The Real Difference Between Data Engineers and Data Scientists?
Automated Machine Learning, AutoML, Books, Data Engineer, Data Scientist, Machine Learning, Python, SQL
- Introduction to Automated Machine Learning - Sep 15, 2021.
AutoML enables developers with limited ML expertise (and coding experience) to train high-quality models specific to their business needs. For this article, we will focus on AutoML systems which cater to everyday business and technology applications.
Automated Machine Learning, AutoML, Machine Learning, Python
- How to Create an AutoML Pipeline Optimization Sandbox - Sep 9, 2021.
In this article, we will implement an automated machine learning pipeline optimization sandbox web app using Streamlit and TPOT.
Automated Machine Learning, AutoML, Python, Streamlit
- Fast AutoML with FLAML + Ray Tune - Sep 6, 2021.
Microsoft Researchers have developed FLAML (Fast Lightweight AutoML) which can now utilize Ray Tune for distributed hyperparameter tuning to scale up FLAML’s resource-efficient & easily parallelizable algorithms across a cluster.
Automated Machine Learning, AutoML, Hyperparameter, Machine Learning, Microsoft, Python, Ray
- Be Wary of Automated Feature Selection — Chi Square Test of Independence Example - Aug 5, 2021.
When Data Scientists use chi square test for feature selection, they just merely go by the ritualistic “If your p-value is low, the null hypothesis must go”. The automated function they use behaves no differently.
Automated Data Science, Automated Machine Learning, Feature Selection, Statistics
- Overview of AutoNLP from Hugging Face with Example Project - Jun 21, 2021.
AutoNLP is a beta project from Hugging Face that builds on the company’s work with its Transformer project. With AutoNLP you can get a working model with just a few simple terminal commands.
Automated Machine Learning, AutoML, Hugging Face, NLP
- Binary Classification with Automated Machine Learning - May 17, 2021.
Check out how to use the open-source MLJAR auto-ML to build accurate models faster.
Automated Machine Learning, AutoML, Classification, Open Source
- Automated Text Classification with EvalML - Apr 6, 2021.
Learn how EvalML leverages Woodwork, Featuretools and the nlp-primitives library to process text data and create a machine learning model that can detect spam text messages.
Automated Machine Learning, AutoML, NLP, Python, Text Analytics, Text Classification
- Easy AutoML in Python - Apr 1, 2021.
We’re excited to announce that a new open-source project has joined the Alteryx open-source ecosystem. EvalML is a library for automated machine learning (AutoML) and model understanding, written in Python.
Automated Machine Learning, AutoML, Machine Learning, Open Source, Python
Google’s Model Search is a New Open Source Framework that Uses Neural Networks to Build Neural Networks - Mar 1, 2021.
The new framework brings state-of-the-art neural architecture search methods to TensorFlow.
Automated Machine Learning, AutoML, Google, Neural Networks, Open Source
- Easy, Open-Source AutoML in Python with EvalML - Feb 16, 2021.
We’re excited to announce that a new open-source project has joined the Alteryx open-source ecosystem. EvalML is a library for automated machine learning (AutoML) and model understanding, written in Python.
Automated Machine Learning, AutoML, Machine Learning, Open Source, Python
15 Free Data Science, Machine Learning & Statistics eBooks for 2021 - Dec 31, 2020.
We present a curated list of 15 free eBooks compiled in a single location to close out the year.
Automated Machine Learning, Data Science, Deep Learning, Free ebook, Machine Learning, NLP, Python, R, Statistics
- Algorithms for Advanced Hyper-Parameter Optimization/Tuning - Nov 17, 2020.
In informed search, each iteration learns from the last, whereas in Grid and Random, modelling is all done at once and then the best is picked. In case for small datasets, GridSearch or RandomSearch would be fast and sufficient. AutoML approaches provide a neat solution to properly select the required hyperparameters that improve the model’s performance.
Automated Machine Learning, AutoML, Hyperparameter, Optimization, Python
- Uber Open Sources the Third Release of Ludwig, its Code-Free Machine Learning Platform - Oct 13, 2020.
The new release makes Ludwig one of the most complete open source AutoML stacks in the market.
Automated Machine Learning, AutoML, Machine Learning, Open Source, Uber
- Build Your Own AutoML Using PyCaret 2.0 - Aug 20, 2020.
In this post we present a step-by-step tutorial on how PyCaret can be used to build an Automated Machine Learning Solution within Power BI, thus allowing data scientists and analysts to add a layer of machine learning to their Dashboards without any additional license or software costs.
Automated Machine Learning, AutoML, Power BI, PyCaret, Python
- Autotuning for Multi-Objective Optimization on LinkedIn’s Feed Ranking - Aug 19, 2020.
In this post, the authors share their experience coming up with an automated system to tune one of the main parameters in their machine learning model that recommends content on LinkedIn’s Feed, which is just one piece of the community-focused architecture.
Automated Machine Learning, AutoML, LinkedIn, Machine Learning, Optimization
- GitHub is the Best AutoML You Will Ever Need - Aug 12, 2020.
This article uses PyCaret 2.0, an open source, low-code machine learning library in Python to develop a simple AutoML solution and deploy it as a Docker container using GitHub actions.
Automated Machine Learning, AutoML, GitHub, PyCaret, Python
Wrapping Machine Learning Techniques Within AI-JACK Library in R - Jul 17, 2020.
The article shows an approach to solving problem of selecting best technique in machine learning. This can be done in R using just one library called AI-JACK and the article shows how to use this tool.
Automated Machine Learning, AutoML, Machine Learning, Modeling, R
Automated Machine Learning: The Free eBook - May 18, 2020.
There is a lot to learn about automated machine learning theory and practice. This free eBook can get you started the right way.
Automated Machine Learning, AutoML, Free ebook, Machine Learning
- Hands on Hyperparameter Tuning with Keras Tuner - Feb 28, 2020.
Or how hyperparameter tuning with Keras Tuner can boost your object classification network's accuracy by 10%.
Automated Machine Learning, AutoML, Keras, Python
- Practical Hyperparameter Optimization - Feb 13, 2020.
An introduction on how to fine-tune Machine and Deep Learning models using techniques such as: Random Search, Automated Hyperparameter Tuning and Artificial Neural Networks Tuning.
Automated Machine Learning, AutoML, Deep Learning, Hyperparameter, Machine Learning, Optimization, Python, scikit-learn
- Amazon Gets Into the AutoML Race with AutoGluon: Some AutoML Architectures You Should Know About - Jan 30, 2020.
Amazon, Microsoft, Salesforce, Waymo have produced some of the most innovative AutoML architectures in the market.
Automated Machine Learning, AutoML, Deep Learning, Machine Learning
- AutoML Poll results: if you try it, you’ll like it more - Jan 27, 2020.
The results of latest KDnuggets Poll on AutoML are quite interesting. While most respondents were not happy with AutoML performance, the opinions of those who tried it were higher than those who did not.
Automated Machine Learning, AutoML, Poll
- H2O Framework for Machine Learning - Jan 6, 2020.
This article is an overview of H2O, a scalable and fast open-source platform for machine learning. We will apply it to perform classification tasks.
Automated Machine Learning, AutoML, H2O, Machine Learning, Python
Automated Machine Learning: How do teams work together on an AutoML project? - Jan 2, 2020.
In this use case, available to the public on GitHub, we’ll see how a data scientist, project manager, and business lead at a retail grocer can leverage automated machine learning and Azure Machine Learning service to reduce product overstock.
Automated Machine Learning, AutoML, Azure ML, Data Science Team, Microsoft, Microsoft Azure
- Google Open Sources MobileNetV3 with New Ideas to Improve Mobile Computer Vision Models - Dec 2, 2019.
The latest release of MobileNets incorporates AutoML and other novel ideas in mobile deep learning.
Automated Machine Learning, Computer Vision, Google, Mobile, Open Source
Automated Machine Learning Project Implementation Complexities - Nov 22, 2019.
To demonstrate the implementation complexity differences along the AutoML highway, let's have a look at how 3 specific software projects approach the implementation of just such an AutoML "solution," namely Keras Tuner, AutoKeras, and automl-gs.
Automated Machine Learning, Keras, Pipeline, Python
- GitHub Repo Raider and the Automation of Machine Learning - Nov 18, 2019.
Since X never, ever marks the spot, this article raids the GitHub repos in search of quality automated machine learning resources. Read on for projects and papers to help understand and implement AutoML.
Automated Machine Learning, GitHub, Machine Learning, Movies, Python
- Using Neural Networks to Design Neural Networks: The Definitive Guide to Understand Neural Architecture Search - Oct 14, 2019.
A recent survey outlined the main neural architecture search methods used to automate the design of deep learning systems.
Architecture, Automated Machine Learning, Neural Networks
- Automate Hyperparameter Tuning for Your Models - Sep 20, 2019.
When we create our machine learning models, a common task that falls on us is how to tune them. So that brings us to the quintessential question: Can we automate this process?
Automated Machine Learning, Hyperparameter, Machine Learning, Modeling
- Can we trust AutoML to go on full autopilot? - Jul 31, 2019.
We put an AutoML tool to the test on a real-world problem, and the results are surprising. Even with automatic machine learning, you still need expert data scientists.
Automated Machine Learning, AutoML, Overfitting, Time Series
- Evolving Deep Neural Networks - Jun 18, 2019.
This article reviews how evolutionary algorithms have been proposed and tested as a competitive alternative to address a number of issues related to neural network design.
Architecture, Automated Machine Learning, Evolutionary Algorithm, Neural Networks
- 3 Reasons Why AutoML Won’t Replace Data Scientists Yet - Mar 6, 2019.
We dispel the myth that AutoML is replacing Data Scientists jobs by highlighting three factors in Data Science development that AutoML can’t solve.
Automated Machine Learning, Automation, AutoML, Data Scientist, Feature Engineering, Reinforcement Learning
- Automatic Machine Learning is broken - Feb 19, 2019.
We take a look at the arguments against implementing a machine learning solution, and the occasions when the problems faced are not ML problems and can perhaps be solved using optimization, exploratory data analysis tasks or problems that can be solved with simple statistics.
Automated Machine Learning, AutoML, Data Preparation, Deployment
- Building AI to Build AI: The Project That Won the NeurIPS AutoML Challenge - Jan 23, 2019.
This is an overview of designing a computer program capable of developing predictive models without any manual intervention that are trained & evaluated in a lifelong machine learning setting in NeurIPS 2018 AutoML3 Challenge.
AI, Automated Machine Learning, AutoML, Gradient Boosting, Hyperparameter, NeurIPS
- Automated Machine Learning in Python - Jan 18, 2019.
An organization can also reduce the cost of hiring many experts by applying AutoML in their data pipeline. AutoML also reduces the amount of time it would take to develop and test a machine learning model.
Automated Machine Learning, AutoML, H2O, Keras, Machine Learning, Python, scikit-learn
- The 6 Most Useful Machine Learning Projects of 2018 - Jan 15, 2019.
Let’s take a look at the top 6 most practically useful ML projects over the past year. These projects have published code and datasets that allow individual developers and smaller teams to learn and immediately create value.
Automated Machine Learning, Facebook, fast.ai, Google, Keras, Machine Learning, Object Detection, Python, Reinforcement Learning, Word Embeddings
- Keras Hyperparameter Tuning in Google Colab Using Hyperas - Dec 12, 2018.
In this post, I will show you how you can tune the hyperparameters of your existing keras models using Hyperas and run everything in a Google Colab Notebook.
Automated Machine Learning, Google, Google Colab, Hyperparameter, Keras, Python
AI, Data Science, Analytics Main Developments in 2018 and Key Trends for 2019 - Dec 3, 2018.
Review of 2018 and Predictions for 2019 from our panel of experts, including Meta Brown, Tom Davenport, Carla Gentry, Bob E Hayes, Cassie Kozyrkov, Doug Laney, Bill Schmarzo, Kate Strachnyi, Ronald van Loon, Favio Vazquez, and Jen Underwood.
2019 Predictions, AI, Automated Machine Learning, Automation, Bill Schmarzo, Carla Gentry, Cassie Kozyrkov, Doug Laney, GDPR, Hype, Jen Underwood, Meta Brown, Predictions, Risks, Ronald van Loon, Tom Davenport, Trends
- Implementing Automated Machine Learning Systems with Open Source Tools - Oct 25, 2018.
What if you want to implement an automated machine learning pipeline of your very own, or automate particular aspects of a machine learning pipeline? Rest assured that there is no need to reinvent any wheels.
Automated Machine Learning, Feature Engineering, Feature Selection, Hyperparameter, Machine Learning, Open Source
- Why Automated Feature Engineering Will Change the Way You Do Machine Learning - Aug 20, 2018.
Automated feature engineering will save you time, build better predictive models, create meaningful features, and prevent data leakage.
Automated Machine Learning, Feature Engineering, Machine Learning, Python
Auto-Keras, or How You can Create a Deep Learning Model in 4 Lines of Code - Aug 17, 2018.
Auto-Keras is an open source software library for automated machine learning. Auto-Keras provides functions to automatically search for architecture and hyperparameters of deep learning models.
Automated Machine Learning, Keras, Neural Networks, Python
Automated Machine Learning vs Automated Data Science - Jul 2, 2018.
Just by adding the term "automated" in front of these 2 separate, distinct concepts does not somehow make them equivalent. Machine learning and data science are not the same thing.
Automated Data Science, Automated Machine Learning, Data Science, Machine Learning
- Deep Feature Synthesis: How Automated Feature Engineering Works - Feb 7, 2018.
Automating feature engineering optimizes the process of building and deploying accurate machine learning models by handling necessary but tedious tasks so data scientists can focus more on other important steps.
Automated Machine Learning, Automation, Data Science, Feature Engineering, Machine Learning
- Using AutoML to Generate Machine Learning Pipelines with TPOT - Jan 29, 2018.
This post will take a different approach to constructing pipelines. Certainly the title gives away this difference: instead of hand-crafting pipelines and hyperparameter optimization, and performing model selection ourselves, we will instead automate these processes.
Automated Machine Learning, Hyperparameter, Optimization, Pipeline, Python, scikit-learn, Workflow
- Using Genetic Algorithm for Optimizing Recurrent Neural Networks - Jan 22, 2018.
In this tutorial, we will see how to apply a Genetic Algorithm (GA) for finding an optimal window size and a number of units in Long Short-Term Memory (LSTM) based Recurrent Neural Network (RNN).
Automated Machine Learning, Genetic Algorithm, Keras, Neural Networks, Python, Recurrent Neural Networks
- Enhancing Anti-Money Laundering Programs with Automated Machine Learning, Jan 11 Webinar - Jan 3, 2018.
In this webinar, Jan 11, DataRobot will show how automated machine learning can be used to reduce false positive rates, thereby improving the efficiency of AML transaction monitoring and reducing costs.
Automated Data Science, Automated Machine Learning, DataRobot, Finance, Money Laundering
Automated Feature Engineering for Time Series Data - Nov 20, 2017.
We introduce a general framework for developing time series models, generating features and preprocessing the data, and exploring the potential to automate this process in order to apply advanced machine learning algorithms to almost any time series problem.
Automated Machine Learning, Data Preparation, Feature Engineering, Feature Selection, Time Series
- TPOT Automated Machine Learning Competition: Can AutoML beat humans on Kaggle? - Jun 5, 2017.
Over the next couple months, we’re going to challenge you to apply TPOT to any data science problem you find interesting on Kaggle. If your entry ranks in the top 25% of the leaderboard on a Kaggle problem, we want to see how TPOT helped you accomplish that.
Automated Data Science, Automated Machine Learning, Competition, Machine Learning
- 5 Machine Learning Projects You Can No Longer Overlook, May - May 10, 2017.
In this month's installment of Machine Learning Projects You Can No Longer Overlook, we find some data preparation and exploration tools, a (the?) reinforcement learning "framework," a new automated machine learning library, and yet another distributed deep learning library.
Automated Machine Learning, Data Exploration, Deep Learning, Distributed Systems, Machine Learning, Overlook, Pandas, Reinforcement Learning
- The Current State of Automated Machine Learning - Jan 18, 2017.
What is automated machine learning (AutoML)? Why do we need it? What are some of the AutoML tools that are available? What does its future hold? Read this article for answers to these and other AutoML questions.
Automated, Automated Data Science, Automated Machine Learning, Hyperparameter, Machine Learning
- Automated Machine Learning: An Interview with Randy Olson, TPOT Lead Developer - Oct 28, 2016.
Read an insightful interview with Randy Olson, Senior Data Scientist at University of Pennsylvania Institute for Biomedical Informatics, and lead developer of TPOT, an open source Python tool that intelligently automates the entire machine learning process.
Automated Data Science, Automated Machine Learning, Machine Learning, Python, scikit-learn
Automated Data Science & Machine Learning: An Interview with the Auto-sklearn Team - Oct 4, 2016.
This is an interview with the authors of the recent winning KDnuggets Automated Data Science and Machine Learning blog contest entry, which provided an overview of the Auto-sklearn project. Learn more about the authors, the project, and automated data science.
Automated, Automated Data Science, Automated Machine Learning, Competition, Machine Learning, scikit-learn
- Contest Winner: Winning the AutoML Challenge with Auto-sklearn - Aug 5, 2016.
This post is the first place prize recipient in the recent KDnuggets blog contest. Auto-sklearn is an open-source Python tool that automatically determines effective machine learning pipelines for classification and regression datasets. It is built around the successful scikit-learn library and won the recent AutoML challenge.
Automated, Automated Data Science, Automated Machine Learning, Competition, Hyperparameter, scikit-learn, Weka
- Contest 2nd Place: Automated Data Science and Machine Learning in Digital Advertising - Aug 4, 2016.
This post is an overview of an automated machine learning system in the digital advertising realm. It is an entrant and second-place recipient in the recent KDnuggets blog contest.
Advertising, Automated, Automated Data Science, Automated Machine Learning, Claudia Perlich, Machine Learning
