Search results for deep learning

Found 5182 documents, 13560 searched:

• 5th International Summer School 2020 on Resource-aware Machine Learning (REAML)

  The Resource-aware Machine Learning summer school provides lectures on the latest research in machine learning, with the twist on resource consumption and how these can be reduced. This year it will be held online between 31st of August and 4th of September, and is free of charge. Register now.

  https://www.kdnuggets.com/2020/07/tu-dortmund-summer-school-2020-reaml.html

• Top Stories, Jun 29 – Jul 5: Speed up your Numpy and Pandas with NumExpr Package; Deploy Machine Learning Pipeline on AWS Fargate

  Also: Getting Started with TensorFlow 2; An Introduction to Statistical Learning: The Free eBook; How Much Math do you need in Data Science?; Data Cleaning: The secret ingredient to the success of any Data Science Project

  https://www.kdnuggets.com/2020/07/top-news-week-0629-0705.html

• The Unreasonable Progress of Deep Neural Networks in Natural Language Processing (NLP)

  Natural language processing has made incredible advances through advanced techniques in deep learning. Learn about these powerful models, and find how close (or far away) these approaches are to human-level understanding.

  https://www.kdnuggets.com/2020/06/unreasonable-progress-deep-neural-networks-nlp.html

• An Introduction to Statistical Learning: The Free eBook

  This week's free eBook is a classic of data science, An Introduction to Statistical Learning, with Applications in R. If interested in picking up elementary statistical learning concepts, and learning how to implement them in R, this book is for you.

  https://www.kdnuggets.com/2020/06/introduction-statistical-learning-free-ebook.html

• Machine Learning Engineer vs Data Scientist (Is Data Science Over?)

  What has been happening to the definition of Data Scientist over the past 5 years? Does it still exist or has it morphed into a new version of its old self? Learn more about the recent trends in job descriptions and salaries for data scientists, ML engineers, and others to best understand the best fit for your career trajectory and interests.

  https://www.kdnuggets.com/2020/06/machine-learning-engineer-vs-data-scientist.html

• Tools to Spot Deepfakes and AI-Generated Text

  The technologies that generate deepfake content is at the forefront of manipulating humans. While the research developing these algorithms is fascinating and will lead to powerful tools that enhance the way people create and work, in the wrong hands, these same tools drive misinformation at a scale we can't yet imagine. Stopping these bad actors using awesome tools is in your hands.

  https://www.kdnuggets.com/2020/06/dont-click-this-how-spot-deepfakes.html

• Graph Machine Learning in Genomic Prediction

  This work explores how genetic relationships can be exploited alongside genomic information to predict genetic traits with the aid of graph machine learning algorithms.

  https://www.kdnuggets.com/2020/06/graph-machine-learning-genomic-prediction.html

• Top KDnuggets tweets, Jun 10-16: A Crash Course in Game Theory for #MachineLearning: Classic and New Ideas

  Also: What is the Best #Python IDE for #DataScience?; Best Machine Learning Youtube Videos Under 10 Minutes - KDnuggets; Understanding Machine Learning: The Free eBook - KDnuggets; Math and Architectures of #DeepLearning; Introducing #MLOps, How to Scale #MachineLearning in the Enterprise

  https://www.kdnuggets.com/2020/06/top-tweets-jun10-16.html

• Crop Disease Detection Using Machine Learning and Computer Vision

  Computer vision has tremendous promise for improving crop monitoring at scale. We present our learnings from building such models for detecting stem and wheat rust in crops.

  https://www.kdnuggets.com/2020/06/crop-disease-detection-computer-vision.html

• Best Machine Learning Youtube Videos Under 10 Minutes

  The Youtube videos on this list cover concepts such as what machine learning is, the basics of natural language processing, how computer vision works, and machine learning in video games.

  https://www.kdnuggets.com/2020/06/best-machine-learning-youtube-videos-under-10-minutes.html

• Uber’s Ludwig is an Open Source Framework for Low-Code Machine Learning">Uber’s Ludwig is an Open Source Framework for Low-Code Machine Learning

  The new framework allow developers with minimum experience to create and train machine learning models.

  https://www.kdnuggets.com/2020/06/uber-ludwig-open-source-framework-machine-learning.html

• Understanding Machine Learning: The Free eBook">Understanding Machine Learning: The Free eBook

  Time to get back to basics. This week we have a look at a book on foundational machine learning concepts, Understanding Machine Learning: From Theory to Algorithms.

  https://www.kdnuggets.com/2020/06/understanding-machine-learning-free-ebook.html

• Deploy a Machine Learning Pipeline to the Cloud Using a Docker Container

  In this tutorial, we will use a previously-built machine learning pipeline and Flask app to demonstrate how to deploy a machine learning pipeline as a web app using the Microsoft Azure Web App Service.

  https://www.kdnuggets.com/2020/06/deploy-machine-learning-pipeline-cloud-docker.html

• Upgrading the Brand Mobile App with Machine Learning

  The tech progress in mobile app development, as well as digital enhancements, have created new chances for brands to allure and retain customers. In bridging the individualization gap, Machine Learning comes to the rescue.

  https://www.kdnuggets.com/2020/06/upgrading-brand-mobile-app-machine-learning.html

• How to make AI/Machine Learning models resilient during COVID-19 crisis

  COVID-19-driven concept shift has created concern over the usage of AI/ML to continue to drive business value following cases of inaccurate outputs and misleading results from a variety of fields. Data Science teams must invest effort in post-model tracking and management as well as deploy an agility in the AI/ML process to curb problems related to concept shift.

  https://www.kdnuggets.com/2020/06/ai-ml-models-resilient-covid-19-crisis.html

• Nitpicking Machine Learning Technical Debt

  Technical Debt in software development is pervasive. With machine learning engineering maturing, this classic trouble is unsurprisingly rearing its ugly head. These 25 best practices, first described in 2015 and promptly overshadowed by shiny new ML techniques, are updated for 2020 and ready for you to follow -- and lead the way to better ML code and processes in your organization.

  https://www.kdnuggets.com/2020/06/nitpicking-machine-learning-technical-debt.html

• Upcoming Webinars and Online Events in AI, Data Science, Machine Learning: June

  Here are some interesting upcoming webinar, online events and virtual conferences in in AI, Data Science, and Machine Learning.

  https://www.kdnuggets.com/2020/06/upcoming-webinars-online-events-june.html

• Machine Learning Experiment Tracking

  Why is experiment tracking so important for doing real world machine learning?

  https://www.kdnuggets.com/2020/06/machine-learning-experiment-tracking.html

• Top Stories, May 25-31: Python For Everybody: The Free eBook; Interactive Machine Learning Experiments

  Also: Dataset Splitting Best Practices in Python; 10 Useful Machine Learning Practices For Python Developers; How to Think Like a Data Scientist or Data Analyst; The Best NLP with Deep Learning Course is Free

  https://www.kdnuggets.com/2020/06/top-news-week-0525-0531.html

• 5 Machine Learning Papers on Face Recognition

  This article will highlight some of that research and introduce five machine learning papers on face recognition.

  https://www.kdnuggets.com/2020/05/5-machine-learning-papers-face-recognition.html

• Deepmind’s Gaming Streak: The Rise of AI Dominance

  There is still a long way to go before machine agents match overall human gaming prowess, but Deepmind’s gaming research focus has shown a clear progression of substantial progress.

  https://www.kdnuggets.com/2020/05/deepmind-gaming-ai-dominance.html

• Interactive Machine Learning Experiments

  Dive into experimenting with machine learning techniques using this open-source collection of interactive demos built on multilayer perceptrons, convolutional neural networks, and recurrent neural networks. Each package consists of ready-to-try web browser interfaces and fully-developed notebooks for you to fine tune the training for better performance.

  https://www.kdnuggets.com/2020/05/interactive-machine-learning-experiments.html

• Build and deploy your first machine learning web app">Build and deploy your first machine learning web app

  A beginner’s guide to train and deploy machine learning pipelines in Python using PyCaret.

  https://www.kdnuggets.com/2020/05/build-deploy-machine-learning-web-app.html

• KDnuggets™ News 20:n20, May 20: I Designed My Own ML and AI Degree; Automated Machine Learning: The Free eBook

  How to design your own AI & ML degree; Automated ML: The free ebook; Coding habits for data scientists; Cartoon: The Worst Telemedicine? Math for Programmers; and more.

  https://www.kdnuggets.com/2020/n20.html

• What they do not tell you about machine learning

  There's a lot of excitement out there about machine learning jobs. So, it's always good to start off with a healthy dose of reality and proper expectations.

  https://www.kdnuggets.com/2020/05/not-tell-machine-learning.html

• Top Stories, May 11-17: Start Your Machine Learning Career in Quarantine; AI and Machine Learning for Healthcare

  Also: Satellite Image Analysis with fast.ai for Disaster Recovery; Machine Learning in Power BI using PyCaret; Deep Learning: The Free eBook; 24 Best (and Free) Books To Understand Machine Learning

  https://www.kdnuggets.com/2020/05/top-news-week-0511-0517.html

• Automated Machine Learning: The Free eBook">Automated Machine Learning: The Free eBook

  There is a lot to learn about automated machine learning theory and practice. This free eBook can get you started the right way.

  https://www.kdnuggets.com/2020/05/automated-machine-learning-free-ebook.html

• AI and Machine Learning for Healthcare">AI and Machine Learning for Healthcare

  Traditional business and technology sectors are not the only fields being impacted by AI. Healthcare is a field that is thought to be highly suitable for the applications of AI tools and techniques.

  https://www.kdnuggets.com/2020/05/ai-machine-learning-healthcare.html

• I Designed My Own Machine Learning and AI Degree

  With so many pioneering online resources for open education, check out this organized collection of courses you can follow to become a well-rounded machine learning and AI engineer.

  https://www.kdnuggets.com/2020/05/designed-machine-learning-ai-degree.html

• KDnuggets™ News 20:n19, May 13: Start Your Machine Learning Career in Quarantine; Will Machine Learning Engineers Exist in 10 Years?

  Also: The Elements of Statistical Learning: The Free eBook; Explaining "Blackbox" Machine Learning Models: Practical Application of SHAP; What You Need to Know About Deep Reinforcement Learning; 5 Concepts You Should Know About Gradient Descent and Cost Function; Hyperparameter Optimization for Machine Learning Models

  https://www.kdnuggets.com/2020/n19.html

• The Elements of Statistical Learning: The Free eBook

  Check out this free ebook covering the elements of statistical learning, appropriately titled "The Elements of Statistical Learning."

  https://www.kdnuggets.com/2020/05/elements-statistical-learning-free-ebook.html

• Start Your Machine Learning Career in Quarantine">Start Your Machine Learning Career in Quarantine

  While this quarantine can last two months, make the most of it by starting your career in Machine Learning with this 60-day learning plan.

  https://www.kdnuggets.com/2020/05/machine-learning-career-quarantine.html

• The Architecture Used at LinkedIn to Improve Feature Management in Machine Learning Models

  The new typed feature schema streamlined the reusability of features across thousands of machine learning models.

  https://www.kdnuggets.com/2020/05/architecture-linkedin-feature-management-machine-learning-models.html

• Top April Stories: Mathematics for Machine Learning: The Free eBook; The Super Duper NLP Repo: 100 Ready-to-Run Colab Notebooks,

  Also: Introducing MIDAS: A New Baseline for Anomaly Detection in Graphs; The Super Duper NLP Repo: 100 Ready-to-Run Colab Notebooks; Five Cool Python Libraries for Data Science.

  https://www.kdnuggets.com/2020/05/top-stories-2020-apr.html

• Will Machine Learning Engineers Exist in 10 Years?

  As can be common in many technical fields, the landscape of specialized roles is evolving quickly. With more people learning at least a little machine learning, this could eventually become a common skill set for every software engineer.

  https://www.kdnuggets.com/2020/05/machine-learning-engineers-not-exist-10-years.html

• Hyperparameter Optimization for Machine Learning Models

  Check out this comprehensive guide to model optimization techniques.

  https://www.kdnuggets.com/2020/05/hyperparameter-optimization-machine-learning-models.html

• Beginners Learning Path for Machine Learning">Beginners Learning Path for Machine Learning

  So, you are interested in machine learning? Here is your complete learning path to start your career in the field.

  https://www.kdnuggets.com/2020/05/beginners-learning-path-machine-learning.html

• Microsoft Research Unveils Three Efforts to Advance Deep Generative Models

  Optimus, FQ-GAN and Prevalent bring new ideas to apply generative models at large scale.

  https://www.kdnuggets.com/2020/05/microsoft-research-three-efforts-advance-deep-generative-models.html

• Optimize Response Time of your Machine Learning API In Production

  This article demonstrates how building a smarter API serving Deep Learning models minimizes the response time.

  https://www.kdnuggets.com/2020/05/optimize-response-time-machine-learning-api-production.html

• Top KDnuggets tweets, Apr 22-28: 24 Best (and Free) Books To Understand Machine Learning

  Also: A Concise Course in Statistical Inference: The Free eBook; ML Ops: Machine Learning as an Engineering Discipline; Learning during a crisis (#DataScience 90-day learning challenge) ; Free High-Quality Machine Learning & Data Science Books & Courses: Quarantine Edition

  https://www.kdnuggets.com/2020/04/top-tweets-apr22-28.html

• KDnuggets™ News 20:n17, Apr 29: The Super Duper NLP Repo; Free Machine Learning & Data Science Books & Courses for Quarantine

  Also: Should Data Scientists Model COVID19 and other Biological Events; Learning during a crisis (Data Science 90-day learning challenge); Data Transformation: Standardization vs Normalization; DBSCAN Clustering Algorithm in Machine Learning; Find Your Perfect Fit: A Quick Guide for Job Roles in the Data World

  https://www.kdnuggets.com/2020/n17.html

• 10 Best Machine Learning Textbooks that All Data Scientists Should Read

  Check out these 10 books that can help data scientists and aspiring data scientists learn machine learning today.

  https://www.kdnuggets.com/2020/04/10-best-machine-learning-textbooks-data-scientists.html

• Free High-Quality Machine Learning & Data Science Books & Courses: Quarantine Edition">Free High-Quality Machine Learning & Data Science Books & Courses: Quarantine Edition

  If you find yourself quarantined and looking for free learning materials in the way of books and courses to sharpen your data science and machine learning skills, this collection of articles I have previously written curating such things is for you.

  https://www.kdnuggets.com/2020/04/machine-learning-data-science-books-courses-quarantine.html

• OpenAI Open Sources Microscope and the Lucid Library to Visualize Neurons in Deep Neural Networks

  The new tools shows the potential of data visualizations for understanding features in a neural network.

  https://www.kdnuggets.com/2020/04/openai-open-sources-microscope-lucid-library-neural-networks.html

• State of the Machine Learning and AI Industry

  Enterprises are struggling to launch machine learning models that encapsulate the optimization of business processes. These are now the essential components of data-driven applications and AI services that can improve legacy rule-based business processes, increase productivity, and deliver results. In the current state of the industry, many companies are turning to off-the-shelf platforms to increase expectations for success in applying machine learning.

  https://www.kdnuggets.com/2020/04/machine-learning-ai-industry.html

• Federated Learning: An Introduction

  Improving machine learning models and making them more secure by training on decentralized data.

  https://www.kdnuggets.com/2020/04/federated-learning-introduction.html

• KDnuggets™ News 20:n15, Apr 15: How to Do Hyperparameter Tuning on Any Python Script; 10 Must-read Machine Learning Articles

  Learn how to do hyperparameter tuning on python ML scripts; Read 10 must-read Machine Learning Articles; Understand the process for Data Science project review; see how data science is used to understand COVID-19; and stay safe and healthy!

  https://www.kdnuggets.com/2020/n15.html

• Can Java Be Used for Machine Learning and Data Science?">Can Java Be Used for Machine Learning and Data Science?

  While Python and R have become favorites for building these programs, many organizations are turning to Java application development to meet their needs. Read on to see how, and why.

  https://www.kdnuggets.com/2020/04/java-used-machine-learning-data-science.html

• DeepMind Unveils Agent57, the First AI Agents that Outperforms Human Benchmarks in 57 Atari Games

  The new reinforcement learning agent innovates over previous architectures achieving one of the most important milestones in the AI space.

  https://www.kdnuggets.com/2020/04/deepmind-agent57-atari-games.html

• Upcoming Webinars and online events in AI, Data Science, Machine Learning

  Use the time at home productively and learn something new! We bring you a selection of upcoming interesting webinars and online events on AI, Data Science, Machine Learning, and related topics.

  https://www.kdnuggets.com/2020/04/upcoming-webinars-online-events.html

• 10 Must-read Machine Learning Articles (March 2020)">10 Must-read Machine Learning Articles (March 2020)

  This list will feature some of the recent work and discoveries happening in machine learning, as well as guides and resources for both beginner and intermediate data scientists.

  https://www.kdnuggets.com/2020/04/10-must-read-machine-learning-articles-march-2020.html

• 2 Things You Need to Know about Reinforcement Learning – Computational Efficiency and Sample Efficiency

  Experimenting with different strategies for a reinforcement learning model is crucial to discovering the best approach for your application. However, where you land can have significant impact on your system's energy consumption that could cause you to think again about the efficiency of your computations.

  https://www.kdnuggets.com/2020/04/2-things-reinforcement-learning.html

• Uber Open Sourced Fiber, a Framework to Streamline Distributed Computing for Reinforcement Learning Models

  The new framework simplifies distributed and scalable training for reinforcement learning agents.

  https://www.kdnuggets.com/2020/04/uber-open-sourced-fiber-framework-distributed-computing-reinforcement-learning.html

• KDnuggets™ News 20:n13, Apr 1: Effective visualizations for pandemic storytelling; Machine learning for time series forecasting

  This week, read about the power of effective visualizations for pandemic storytelling; see how (not) to use machine learning for time series forecasting; learn about a deep learning breakthrough: a sub-linear deep learning algorithm that does not need a GPU?; familiarize yourself with how to painlessly analyze your time series; check out what can we learn from the latest coronavirus trends; and... KDnuggets topics?!? Also, much more.

  https://www.kdnuggets.com/2020/n13.html

• Microsoft Research Uses Transfer Learning to Train Real-World Autonomous Drones

  The new research uses policies learned in simulations in real world drone environments.

  https://www.kdnuggets.com/2020/03/microsoft-research-transfer-learning-train-real-world-autonomous-drones.html

• Top Stories, Mar 23-29: 24 Best (and Free) Books To Understand Machine Learning; COVID-19 Visualized: The power of effective visualizations for pandemic storytelling

  Also: Coronavirus Data and Poll Analysis – yes, there is hope, if we act now; Making sense of ensemble learning techniques; Nine lessons learned during my first year as a Data Scientist; Deep Learning Breakthrough: a sub-linear deep learning algorithm that does not need a GPU?

  https://www.kdnuggets.com/2020/03/top-news-week-0323-0329.html

• Making sense of ensemble learning techniques

  This article breaks down ensemble learning and how it can be used for problem solving.

  https://www.kdnuggets.com/2020/03/making-sense-ensemble-learning-techniques.html

• Diffusion Map for Manifold Learning, Theory and Implementation

  This article aims to introduce one of the manifold learning techniques called Diffusion Map. This technique enables us to understand the underlying geometric structure of high dimensional data as well as to reduce the dimensions, if required, by neatly capturing the non-linear relationships between the original dimensions.

  https://www.kdnuggets.com/2020/03/diffusion-map-manifold-learning-theory-implementation.html

• KDnuggets™ News 20:n12, Mar 25: 24 Best (and Free) Books To Understand Machine Learning; Coronavirus Daily Change and Poll Analysis; 9 lessons learned during 1st year as a Data Scientist

  Read our analysis of coronavirus data and poll results; Use your time indoors to learn with 24 best and free books to understand Machine Learning; Study the 9 important lessons from the first year as a Data Scientist; Understand the SVM, a top ML algorithm; check a comprehensive list of AI resources for online learning; and more.

  https://www.kdnuggets.com/2020/n12.html

• Top AI Resources – Directory for Remote Learning

  Whether you are just learning Data Science, a current professional, or just interested, it's crucial to keep the mind stimulated and stay current. With conferences, schools, and travel largely canceled because of #coronavirus, these remote resources will help you stay engaged.

  https://www.kdnuggets.com/2020/03/top-ai-resources-remote-learning.html

• Top Stories, Mar 16-22: 24 Best (and Free) Books To Understand Machine Learning

  Also: Time Series Classification Synthetic vs Real Financial Time Series; Nine lessons learned during my first year as a Data Scientist; What is the most effective policy response to the new coronavirus pandemic?; Nine lessons learned during my first year as a Data Scientist; Five Interesting Data Engineering Projects

  https://www.kdnuggets.com/2020/03/top-news-week-0316-0322.html

• Exploring TensorFlow Quantum, Google’s New Framework for Creating Quantum Machine Learning Models

  TensorFlow Quantum allow data scientists to build machine learning models that work on quantum architectures.

  https://www.kdnuggets.com/2020/03/tensorflow-quantum-framework-quantum-machine-learning-models.html

• Building a Mature Machine Learning Team

  After spending a lot of time thinking about the paths that software companies take toward ML maturity, this framework was created to follow as you adopt ML and then mature as an organization. The framework covers every aspect of building a team including product, process, technical, and organizational readiness, as well as recognizes the importance of cross-functional expertise and process improvements for bringing AI-driven products to market.

  https://www.kdnuggets.com/2020/03/mature-machine-learning-team.html

• The Most Useful Machine Learning Tools of 2020

  This articles outlines 5 sets of tools every lazy full-stack data scientist should use.

  https://www.kdnuggets.com/2020/03/most-useful-machine-learning-tools-2020.html

• Decision Boundary for a Series of Machine Learning Models

  I train a series of Machine Learning models using the iris dataset, construct synthetic data from the extreme points within the data and test a number of Machine Learning models in order to draw the decision boundaries from which the models make predictions in a 2D space, which is useful for illustrative purposes and understanding on how different Machine Learning models make predictions.

  https://www.kdnuggets.com/2020/03/decision-boundary-series-machine-learning-models.html

• Few-Shot Image Classification with Meta-Learning

  Here is how you can teach your model to learn quickly from a few examples.

  https://www.kdnuggets.com/2020/03/few-shot-image-classification-meta-learning.html

• Google Open Sources TFCO to Help Build Fair Machine Learning Models

  A new optimization framework helps to incorporate fairness constraints in machine learning models.

  https://www.kdnuggets.com/2020/03/google-open-sources-tfco-fair-machine-learning-models.html

• Top KDnuggets tweets, Mar 04-10: 10 Free Must-Read Books for Machine Learning and Data Science

  Also: The three phases of #COVID19 – and how we can make it manageable; 50 Must-Read Free Books For Every Data Scientist in 2020; Binary classification is a core machine learning technique, but is there a better way to evaluate its performance than ROC-AUC?

  https://www.kdnuggets.com/2020/03/top-tweets-mar04-10.html

• Software Interfaces for Machine Learning Deployment

  While building a machine learning model might be the fun part, it won't do much for anyone else unless it can be deployed into a production environment. How to implement machine learning deployments is a special challenge with differences from traditional software engineering, and this post examines a fundamental first step -- how to create software interfaces so you can develop deployments that are automated and repeatable.

  https://www.kdnuggets.com/2020/03/software-interfaces-machine-learning-deployment.html

• New Poll: Coronavirus impact on AI/Data Science/Machine Learning community">New Poll: Coronavirus impact on AI/Data Science/Machine Learning community

  Has coronavirus impacted your conference or other travel plans, and do you anticipate it causing further professional or educational disruption in the near future? Take part in the new KDnuggets poll and have your say.

  https://www.kdnuggets.com/2020/03/poll-coronavirus-impact-data-science-community.html

• 21 Machine Learning Projects – Datasets Included

  Upgrading your machine learning, AI, and Data Science skills requires practice. To practice, you need to develop models with a large amount of data. Finding good datasets to work with can be challenging, so this article discusses more than 20 great datasets along with machine learning project ideas for you to tackle today.

  https://www.kdnuggets.com/2020/03/20-machine-learning-datasets-project-ideas.html

• A Crash Course in Game Theory for Machine Learning: Classic and New Ideas

  Game theory is experiencing a renaissance driven by the evolution of AI. What are some classic and new ideas that data scientists should be aware of.

  https://www.kdnuggets.com/2020/03/crash-course-game-theory-machine-learning.html

• Phishytics – Machine Learning for Detecting Phishing Websites

  Since phishing is such a widespread problem in the cybersecurity domain, let us take a look at the application of machine learning for phishing website detection.

  https://www.kdnuggets.com/2020/03/phishytics-machine-learning-detecting-phishing-websites.html

• Top KDnuggets tweets, Feb 26 – Mar 03: Free Mathematics Courses for #DataScience & #MachineLearning

  Also What is the Best #Python IDE for #DataScience? A Crash Course in Game Theory for Machine Learning: Classic and New Ideas; Statistical Modelling vs #MachineLearning.

  https://www.kdnuggets.com/2020/03/top-tweets-feb26-mar03.html

• The Augmented Scientist Part 1: Practical Application Machine Learning in Classification of SEM Images

  Our goal here is to see if we can build a classifier that can identify patterns in Scanning Electron Microscope (SEM) images, and compare the performance of our classifier to the current state-of-the-art.

  https://www.kdnuggets.com/2020/03/the-augmented-scientist-practical-application-machine-learning-classification-images.html

• Top Stories, Feb 24 – Mar 1: Learning from 3 big Data Science career mistakes; Free Mathematics Courses for Data Science & Machine Learning

  Also: The Death of Data Scientists — will AutoML replace them?; Probability Distributions in Data Science; The Big Bad NLP Database: Access Nearly 300 Datasets;; Leaders, Changes, and Trends in Gartner 2020 Magic Quadrant for Data Science and Machine Learning Platforms; New Poll: When Will AutoML Replace Data Scientists (if ever)?

  https://www.kdnuggets.com/2020/03/top-news-week-0224-0301.html

• 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 2)">20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 2)

  We explain important AI, ML, Data Science terms you should know in 2020, including Double Descent, Ethics in AI, Explainability (Explainable AI), Full Stack Data Science, Geospatial, GPT-2, NLG (Natural Language Generation), PyTorch, Reinforcement Learning, and Transformer Architecture.

  https://www.kdnuggets.com/2020/03/ai-data-science-machine-learning-key-terms-part2.html

• Uber Unveils a New Service for Backtesting Machine Learning Models at Scale

  The transportation giant built a new service and architecture for backtesting forecasting models.

  https://www.kdnuggets.com/2020/03/uber-unveils-service-backtesting-machine-learning-models-scale.html

• KDnuggets™ News 20:n08, Feb 26: Gartner 2020 Magic Quadrant for Data Science & Machine Learning Platforms; Will AutoML Replace Data Scientists?

  This week in KDnuggets: The Death of Data Scientists - will AutoML replace them?; Leaders, Changes, and Trends in Gartner 2020 Magic Quadrant for Data Science and Machine Learning Platforms; Hand labeling is the past. The future is #NoLabel AI; The Forgotten Algorithm; Getting Started with R Programming; and much, much more.

  https://www.kdnuggets.com/2020/n08.html

• Learning from 3 big Data Science career mistakes">Learning from 3 big Data Science career mistakes

  Thinking of data science as merely a technical profession, like programming, may take you away from your goals. We explain big mistakes to avoid, including not understanding the 2 cultures of statistics, and not understanding the shift to industrial focus.

  https://www.kdnuggets.com/2020/02/learning-from-big-data-science-career-mistakes.html

• Leaders, Changes, and Trends in Gartner 2020 Magic Quadrant for Data Science and Machine Learning Platforms">Leaders, Changes, and Trends in Gartner 2020 Magic Quadrant for Data Science and Machine Learning Platforms

  The Gartner 2020 Magic Quadrant for Data Science and Machine Learning Platforms has the largest number of leaders ever. We examine the leaders and changes and trends vs previous years.

  https://www.kdnuggets.com/2020/02/gartner-mq-2020-data-science-machine-learning.html

• Microsoft Open Sources ZeRO and DeepSpeed: The Technologies Behind the Biggest Language Model in History

  The two efforts enable the training of deep learning models at massive scale.

  https://www.kdnuggets.com/2020/02/microsoft-open-sources-zero-deepspeed-language-model.html

• Prepare for a Long Battle against Deepfakes

  While deepfakes threaten to destroy our perception of reality, the tech giants are throwing down the gauntlet and working to enhance the state of the art in combating doctored videos and images.

  https://www.kdnuggets.com/2020/02/long-battle-against-deepfakes.html

• Top KDnuggets tweets, Feb 12-18: What Does it Mean to Deploy a #MachineLearning Model?

  Also: A minimalist drawing that represents closeness over time. Captures the span of life with bittersweet accuracy; How much is a Data Scientist's salary in 2020?; Great set of #NLP Interview Questions #DeepLearning; 12-Hour Machine Learning Challenge: Build & deploy an app with Streamlit and DevOps tools

  https://www.kdnuggets.com/2020/02/top-tweets-feb12-18.html

• KDnuggets™ News 20:n07, Feb 19: 20 AI, Data Science, Machine Learning Terms for 2020; Why Did I Reject a Data Scientist Job?

  This week on KDnuggets: 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020; Why Did I Reject a Data Scientist Job?; Fourier Transformation for a Data Scientist; Math for Programmers; Deep Neural Networks; Practical Hyperparameter Optimization; and much more!

  https://www.kdnuggets.com/2020/n07.html

• 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 1)">20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 1)

  2020 is well underway, and we bring you 20 AI, data science, and machine learning terms we should all be familiar with as the year marches onward.

  https://www.kdnuggets.com/2020/02/ai-data-science-machine-learning-key-terms-2020.html

• Inside The Machine Learning that Google Used to Build Meena: A Chatbot that Can Chat About Anything

  Meena is one of the major milestones in the history of NLU. How did Google build it?

  https://www.kdnuggets.com/2020/02/inside-machine-learning-google-build-meena-chatbot.html

• Deep Neural Networks

  We examine the features and applications of a deep neural network.

  https://www.kdnuggets.com/2020/02/deep-neural-networks.html

• What Does it Mean to Deploy a Machine Learning Model?

  You are a Data Scientist who knows how to develop machine learning models. You might also be a Data Scientist who is too afraid to ask how to deploy your machine learning models. The answer isn't entirely straightforward, and so is a major pain point of the community. This article will help you take a step in the right direction for production deployments that are automated, reproducible, and auditable.

  https://www.kdnuggets.com/2020/02/deploy-machine-learning-model.html

• Sharing your machine learning models through a common API

  DEEPaaS API is a software component developed to expose machine learning models through a REST API. In this article we describe how to do it.

  https://www.kdnuggets.com/2020/02/sharing-machine-learning-models-common-api.html

• Amazon Uses Self-Learning to Teach Alexa to Correct its Own Mistakes

  The digital assistant incorporates a reformulation engine that can learn to correct responses in real time based on customer interactions.

  https://www.kdnuggets.com/2020/02/amazon-uses-self-learning-teach-alexa-correct-mistakes.html

• Intro to Machine Learning and AI based on high school knowledge

  Machine learning information is becoming pervasive in the media as well as a core skill in new, important job sectors. Getting started in the field can require learning complex concepts, and this article outlines an approach on how to begin learning about these exciting topics based on high school knowledge.

  https://www.kdnuggets.com/2020/02/intro-machine-learning-ai.html

• Why are Machine Learning Projects so Hard to Manage?

  What makes deploying a machine learning project so difficult? Is it the expectations? The people? The tech? There are common threads to these challenges, and best practices exist to deal with them.

  https://www.kdnuggets.com/2020/02/machine-learning-projects-manage.html

• Microsoft Open Sources Jericho to Train Reinforcement Learning Using Linguistic Games

  The new framework provides an OpenAI-like environment for language-based games.

  https://www.kdnuggets.com/2020/02/microsoft-open-sources-jericho-reinforcement-learning-linguistic-games.html

• Past 2020 Meetings / Online Events on AI, Analytics, Big Data, Data Science, and Machine Learning

  Past | Jan | Feb | Mar | Apr | May | Jun | Jul | Aug | Sep | Oct | Nov | Dec Read more »

  https://www.kdnuggets.com/meetings/past-meetings-2020.html

• Data Validation for Machine Learning">Data Validation for Machine Learning

  While the validation process cannot directly find what is wrong, the process can show us sometimes that there is a problem with the stability of the model.

  https://www.kdnuggets.com/2020/01/data-validation-machine-learning.html

• Top 10 AI, Machine Learning Research Articles to know">Top 10 AI, Machine Learning Research Articles to know

  We’ve seen many predictions for what new advances are expected in the field of AI and machine learning. Here, we review a “data set” based on what researchers were apparently studying at the turn of the decade to take a fresh glimpse into what might come to pass in 2020.

  https://www.kdnuggets.com/2020/01/top-10-ai-ml-articles-to-know.html

• Managing Machine Learning Cycles: Five Learnings from comparing Data Science Experimentation/ Collaboration Tools

  Machine learning projects require handling different versions of data, source code, hyperparameters, and environment configuration. Numerous tools are on the market for managing this variety, and this review features important lessons learned from an ongoing evaluation of the current landscape.

  https://www.kdnuggets.com/2020/01/managing-machine-learning-cycles.html

• Semi-supervised learning with Generative Adversarial Networks

  The paper discussed in this post, Semi-supervised learning with Generative Adversarial Networks, utilizes a GAN architecture for multi-label classification.

  https://www.kdnuggets.com/2020/01/semi-supervised-learning-generative-adversarial-networks.html

• Random Forest® — A Powerful Ensemble Learning Algorithm

  The article explains the Random Forest algorithm and how to build and optimize a Random Forest classifier.

  https://www.kdnuggets.com/2020/01/random-forest-powerful-ensemble-learning-algorithm.html

• The Future of Machine Learning

  This summary overviews the keynote at TensorFlow World by Jeff Dean, Head of AI at Google, that considered the advancements of computer vision and language models and predicted the direction machine learning model building should follow for the future.

  https://www.kdnuggets.com/2020/01/future-machine-learning.html

• Classify A Rare Event Using 5 Machine Learning Algorithms

  Which algorithm works best for unbalanced data? Are there any tradeoffs?

  https://www.kdnuggets.com/2020/01/classify-rare-event-machine-learning-algorithms.html

• KDnuggets™ News 20:n02, Jan 15: Top 5 Must-have Data Science Skills; Learn Machine Learning with THIS Book

  This week: learn the 5 must-have data science skills for the new year; find out which book is THE book to get started learning machine learning; pick up some Python tips and tricks; learn SQL, but learn it the hard way; and find an introductory guide to learning common NLP techniques.

  https://www.kdnuggets.com/2020/n02.html

• Graph Machine Learning Meets UX: An uncharted love affair

  When machine learning tools are developed by technology first, they risk failing to deliver on what users actually need. It can also be difficult for development teams to establish meaningful direction. This article explores the challenges of designing an interface that enables users to visualise and interact with insights from graph machine learning, and explores the very new, uncharted relationship between machine learning and UX.

  https://www.kdnuggets.com/2020/01/graph-machine-learning-ux.html

• Uber Creates Generative Teaching Networks to Better Train Deep Neural Networks

  The new technique can really improve how deep learning models are trained at scale.

  https://www.kdnuggets.com/2020/01/uber-generative-teaching-networks-train-neural-networks.html

• Deepfakes Security Risks

  Deepfakes have instilled panic in experts since they first emerged in 2017. Microsoft and Facebook have recently announced a contest to identify deepfakes more efficiently.

  https://www.kdnuggets.com/2020/01/deepfakes-security-risks.html

• The Book to Start You on Machine Learning">The Book to Start You on Machine Learning

  This book is thought for beginners in Machine Learning, that are looking for a practical approach to learning by building projects and studying the different Machine Learning algorithms within a specific context.

  https://www.kdnuggets.com/2020/01/book-start-machine-learning.html

• Introducing Generalized Integrated Gradients (GIG): A Practical Method for Explaining Diverse Ensemble Machine Learning Models

  There is a need for a new way to explain complex, ensembled ML models for high-stakes applications such as credit and lending. This is why we invented GIG.

  https://www.kdnuggets.com/2020/01/generalized-integrated-gradients-explaining-ensemble-models.html

• H2O Framework for Machine Learning

  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.

  https://www.kdnuggets.com/2020/01/h2o-framework-machine-learning.html

• Top Stories, Dec 30 – Jan 5: How To Ultralearn Data Science; Automated Machine Learning: How do teams work together on an AutoML project?

  Also: Predict Electricity Consumption Using Time Series Analysis; What is the most important question for Data Science (and Digital Transformation); Why Python is One of the Most Preferred Languages for Data Science?; What is a Data Scientist Worth?; How to Speed up Pandas by 4x with one line of code

  https://www.kdnuggets.com/2020/01/top-news-week-1230-0105.html

• How To “Ultralearn” Data Science: deep understanding and experimentation, Part 4

  In this fourth and final part of the ultralearning data science series, it's time to take the final steps toward developing a deep understanding of the fundamentals and learning how to experiment -- the two aspects that are the ultimate keys to ultralearning.

  https://www.kdnuggets.com/2019/12/ultralearn-data-science-deep-understanding-experimentation-part4.html

• 10 Best and Free Machine Learning Courses, Online

  Getting ready to leap into the world of Data Science? Consider these top machine learning courses curated by experts to help you learn and thrive in this exciting field.

  https://www.kdnuggets.com/2019/12/best-free-machine-learning-courses-online.html

• How To “Ultralearn” Data Science: optimization learning, Part 3

  This third part in a series about how to "ultralearn" data science will guide you through how to optimize your learning through five valuable techniques.

  https://www.kdnuggets.com/2019/12/ultralearn-data-science-optimization-learning-part3.html

• Industry AI, Analytics, Machine Learning, Data Science Predictions for 2020

  Predictions for 2020 from a dozen innovative companies in AI, Analytics, Machine Learning, Data Science, and Data industry.

  https://www.kdnuggets.com/2019/12/predictions-ai-machine-learning-data-science-industry.html

• Top Stories, Dec 9-15: Machine Learning & Data Science Research Main Developments, Key Trends; Build Pipelines with Pandas Using pdpipe

  Also: Plotnine: Python Alternative to ggplot2; AI, Analytics, Machine Learning, Data Science, Deep Learning Technology Main Developments in 2019 and Key Trends for 2020; Moving Predictive Maintenance from Theory to Practice; 10 Free Top Notch Machine Learning Courses; Math for Programmers!

  https://www.kdnuggets.com/2019/12/top-news-week-1209-1215.html

• Microsoft Introduces Icebreaker to Address the Famous Ice-Start Challenge in Machine Learning

  The new technique allows the deployment of machine learning models that operate with minimum training data.

  https://www.kdnuggets.com/2019/12/microsoft-introduces-icebreaker-ice-start-challenge-machine-learning.html

• Xavier Amatriain’s Machine Learning and Artificial Intelligence 2019 Year-end Roundup

  It is an annual tradition for Xavier Amatriain to write a year-end retrospective of advances in AI/ML, and this year is no different. Gain an understanding of the important developments of the past year, as well as insights into what expect in 2020.

  https://www.kdnuggets.com/2019/12/xavier-amatriain-machine-learning-ai-year-end-roundup.html

• KDnuggets™ News 19:n47, Dec 11: 10 Free Top Notch Machine Learning Courses; AI, Analytics, ML, DS Main Developments and Key Trends

  We asked top experts: What were the main developments in AI, Data Science, Deep Learning, and Machine Learning Research in 2019, and what key trends do you expect in 2020? Read their answers, and also check 10 Free Top Notch Machine Learning Courses; 4 Hottest Trends in Data Science; The Essential Toolbox for Data Cleaning, and more

  https://www.kdnuggets.com/2019/n47.html

• Scalable graph machine learning: a mountain we can climb?

  Graph machine learning is a developing area of research that brings many complexities. One challenge that both fascinates and infuriates those working with graph algorithms is — scalability. We take a close look at scalability for graph machine learning methods covering what it is, what makes it difficult, and an example of a method that tackles it head-on.

  https://www.kdnuggets.com/2019/12/scalable-graph-machine-learning.html

• Top Stories, Dec 2-8: How to Speed up Pandas by 4x with one line of code; 10 Free Top Notch Machine Learning Courses

  Also: Data Science Curriculum Roadmap; Enabling the Deep Learning Revolution; The Essential Toolbox for Data Cleaning; A Non-Technical Reading List for Data Science; The Future of Careers in Data Science & Analysis

  https://www.kdnuggets.com/2019/12/top-news-week-1202-1208.html

• DeepMind Unveils MuZero, a New Agent that Mastered Chess, Shogi, Atari and Go Without Knowing the Rules

  The new model showed great improvements over the previous AlphaZero agent.

  https://www.kdnuggets.com/2019/12/deepmind-unveils-muzero-agent-chess-shogi-atari-go.html

• 10 Free Top Notch Machine Learning Courses">10 Free Top Notch Machine Learning Courses

  Are you interested in studying machine learning over the holidays? This collection of 10 free top notch courses will allow you to do just that, with something for every approach to improving your machine learning skills.

  https://www.kdnuggets.com/2019/12/10-free-top-notch-courses-machine-learning.html

• Why software engineering processes and tools don’t work for machine learning

  While AI may be the new electricity significant challenges remain to realize AI potential. Here we examine why data scientists and teams can’t rely on software engineering tools and processes for machine learning.

  https://www.kdnuggets.com/2019/12/comet-software-engineering-machine-learning.html

• Lit BERT: NLP Transfer Learning In 3 Steps

  PyTorch Lightning is a lightweight framework which allows anyone using PyTorch to scale deep learning code easily while making it reproducible. In this tutorial we’ll use Huggingface's implementation of BERT to do a finetuning task in Lightning.

  https://www.kdnuggets.com/2019/11/lit-bert-nlp-transfer-learning-3-steps.html

• Machine Learning 101: The What, Why, and How of Weighting

  Weighting is a technique for improving models. In this article, learn more about what weighting is, why you should (and shouldn’t) use it, and how to choose optimal weights to minimize business costs.

  https://www.kdnuggets.com/2019/11/machine-learning-what-why-how-weighting.html

• Probability Learning: Naive Bayes

  This post will describe various simplifications of Bayes' Theorem, that make it more practical and applicable to real world problems: these simplifications are known by the name of Naive Bayes. Also, to clarify everything we will see a very illustrative example of how Naive Bayes can be applied for classification.

  https://www.kdnuggets.com/2019/11/probability-learning-naive-bayes.html

• Automated Machine Learning Project Implementation Complexities">Automated Machine Learning Project Implementation Complexities

  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.

  https://www.kdnuggets.com/2019/11/automl-implementation-complexities.html

• Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead">Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead

  The two main takeaways from this paper: firstly, a sharpening of my understanding of the difference between explainability and interpretability, and why the former may be problematic; and secondly some great pointers to techniques for creating truly interpretable models.

  https://www.kdnuggets.com/2019/11/stop-explaining-black-box-models.html

• KDnuggets™ News 19:n44, Nov 20: How I Got Better at Machine Learning; Tips for a cost-effective ML project

  Read tips and tricks that helped one Data Scientist to get better at Machine Learning; Learn how to make ML project cost-effective; Consider submitting a blog to KDnuggets - you can be profiled here; and study how to manipulate Python lists.

  https://www.kdnuggets.com/2019/n44.html

• The Reinforcement-Learning Methods that Allow AlphaStar to Outcompete Almost All Human Players at StarCraft II

  The new AlphaStar achieved Grandmaster level at StarCraft II overcoming some of the limitations of the previous version. How did it do it?

  https://www.kdnuggets.com/2019/11/reinforcement-learning-methods-alphastar-outcompete-human-players-starcraft.html