Search results for deep learning

Found 5024 documents, 13057 searched:

• How to Learn Math for Machine Learning

  So how much math do you need to know in order to work in the data science industry? The answer: Not as much as you think.

  https://www.kdnuggets.com/2022/02/learn-math-machine-learning.html

• Top Posts Jan 31 – Feb 6: 7 Steps to Mastering Machine Learning with Python in 2022

  Also: How to Write SQL in Native Python; The High Paying Side Hustles for Data Scientists; Top Programming Languages and Their Uses; Is Data Science a Dying Career?

  https://www.kdnuggets.com/2022/02/top-news-week-0131-0206.html

• 7 Steps to Mastering Machine Learning with Python in 2022

  Are you trying to teach yourself machine learning from scratch, but aren’t sure where to start? I will attempt to condense all the resources I’ve used over the years into 7 steps that you can follow to teach yourself machine learning.

  https://www.kdnuggets.com/2022/02/7-steps-mastering-machine-learning-python.html

• TensorFlow for Computer Vision – Transfer Learning Made Easy

  In this article, see how you can get above 90% accuracy on the validation set with a pretty straightforward approach. You'll also see what happens to the validation accuracy if we scale down the amount of training data by a factor of 20. Spoiler alert - it will remain unchanged.

  https://www.kdnuggets.com/2022/01/tensorflow-computer-vision-transfer-learning-made-easy.html

• Learn Machine Learning 4X Faster by Participating in Competitions

  Participating in competitions has taught me everything about machine learning and how It can help you learn multiple domains faster than online courses.

  https://www.kdnuggets.com/2022/01/learn-machine-learning-4x-faster-participating-competitions.html

• KDnuggets™ News 22:n03, Jan 19: A Deep Look Into 13 Data Scientist Roles and Their Responsibilities; Top Five SQL Window Functions You Should Know For Data Science Interviews

  A Deep Look Into 13 Data Scientist Roles and Their Responsibilities; Top Five SQL Window Functions You Should Know For Data Science Interviews; 5 Things to Keep in Mind Before Selecting Your Next Data Science Job; Models Are Rarely Deployed: An Industry-wide Failure in Machine Learning Leadership; Running Redis on Google Colab

  https://www.kdnuggets.com/2022/n03.html

• Models Are Rarely Deployed: An Industry-wide Failure in Machine Learning Leadership

  In this article, Eric Siegel summarizes the recent KDnuggets poll results and argues that the pervasive failure of ML projects comes from a lack of prudent leadership. He also argues that MLops is not the fundamental missing ingredient – instead, an effective ML leadership practice must be the dog that wags the model-integration tail.

  https://www.kdnuggets.com/2022/01/models-rarely-deployed-industrywide-failure-machine-learning-leadership.html

• Transfer Learning for Image Recognition and Natural Language Processing

  Read the second article in this series on Transfer Learning, and learn how to apply it to Image Recognition and Natural Language Processing.

  https://www.kdnuggets.com/2022/01/transfer-learning-image-recognition-natural-language-processing.html

• A Deep Look Into 13 Data Scientist Roles and Their Responsibilities

  Any modern company of any significant size around the world has a data science department, and a data engineer at one company might have the same responsibilities as a marketing scientist at another company. Data science jobs are not well-labeled, so make sure to cast a wide net.

  https://www.kdnuggets.com/2022/01/deep-look-13-data-scientist-roles-responsibilities.html

• What is Transfer Learning?

  During transfer learning, the knowledge leveraged and rapid progress from a source task is used to improve the learning and development to a new target task. Read on for a deeper dive on the subject.

  https://www.kdnuggets.com/2022/01/transfer-learning.html

• Why are More Developers Using Python for Their Machine Learning Projects?

  To support the creation of new and exciting ML and artificial intelligence (AI) applications, developers need a robust programming language. That's where the Python programming language comes in.

  https://www.kdnuggets.com/2022/01/developers-python-machine-learning-projects.html

• Hands-on Reinforcement Learning Course Part 3: SARSA

  This is part 3 of my hands-on course on reinforcement learning, which takes you from zero to HERO . Today we will learn about SARSA, a powerful RL algorithm.

  https://www.kdnuggets.com/2022/01/handson-reinforcement-learning-course-part-3-sarsa.html

• 4 Reasons Why You Shouldn’t Use Machine Learning

  It's time to learn: machine learning is not a Swiss Army knife.

  https://www.kdnuggets.com/2021/12/4-reasons-shouldnt-machine-learning.html

• Explainable Forecasting and Nowcasting with State-of-the-art Deep Neural Networks and Dynamic Factor Model

  Review this detailed tutorial with code and revisit the decades-long old problem using a democratized and interpretable AI framework of how precisely can we anticipate the future and understand its causal factors?

  https://www.kdnuggets.com/2021/12/sota-explainable-forecasting-and-nowcasting.html

• Hands-On Reinforcement Learning Course, Part 1

  Start your learning journey in Reinforcement Learning with this first of two part tutorial that covers the foundations of the technique with examples and Python code.

  https://www.kdnuggets.com/2021/12/hands-on-reinforcement-learning-course-part-1.html

• Federated Learning: Collaborative Machine Learning with a Tutorial on How to Get Started

  Read on to learn more about the intricacies of federated learning and what it can do for machine learning on sensitive data.

  https://www.kdnuggets.com/2021/12/federated-learning-collaborative-machine-learning-tutorial-get-started.html

• Top Resources for Learning Statistics for Data Science">Top Resources for Learning Statistics for Data Science

  Let’s take a look at the current state of statistics in data science, and what you can do to accelerate your learning.

  https://www.kdnuggets.com/2021/12/springboard-top-resources-learn-data-science-statistics.html

• KDnuggets™ News 21:n47, Dec 15: Building a solid data team; Stop Learning Data Science to Find Purpose and Find Purpose to Learn Data Science; AI, Analytics, Machine Learning, Data Science Main Developments in 2021 and Key Trends for 2022

  In this issue: Building a solid data team; Stop Learning Data Science to Find Purpose and Find Purpose to Learn Data Science; AI, Analytics, Machine Learning, Data Science, Deep Learning Main Developments in 2021 and Key Trends for 2022 - Research, Technology, and Industry perspectives.

  https://www.kdnuggets.com/2021/n47.html

• Data Labeling for Machine Learning: Market Overview, Approaches, and Tools

  So much of data science and machine learning is founded on having clean and well-understood data sources that it is unsurprising that the data labeling market is growing faster than ever. Here, we highlight many of the top players in this industry and the techniques they use to help you consider which might make a good partner for your needs.

  https://www.kdnuggets.com/2021/12/data-labeling-ml-overview-and-tools.html

• Main 2021 Developments and Key 2022 Trends in AI, Data Science, Machine Learning Technology

  Our panel of leading experts reviews 2021 main developments and examines the key trends in AI, Data Science, Machine Learning, and Deep Learning Technology.

  https://www.kdnuggets.com/2021/12/trends-ai-data-science-ml-technology.html

• Deep Neural Networks Don’t Lead Us Towards AGI

  Machine learning techniques continue to evolve with increased efficiency for recognition problems. But, they still lack the critical element of intelligence, so we remain a long way from attaining AGI.

  https://www.kdnuggets.com/2021/12/deep-neural-networks-not-toward-agi.html

• Meta-Learning for Keyphrase Extraction

  This article explores Meta-Learning for Key phrase Extraction, which delves into the how and why of KeyPhrase Extraction (KPE) - extracting phrases/groups of words from a document to best capture and represent its content. The article outline what needs to be done to build a keyphrase extractor that performs well not only on in-domain data, but also in a zero-shot scenario where keyphrases need to be extracted from data that have a different distribution (either a different domain or a different type of documents).

  https://www.kdnuggets.com/2021/12/metalearning-keyphrase-extraction.html

• KDnuggets™ News 21:n45, Dec 1: Most Common SQL Mistakes on Data Science Interviews; Why Machine Learning Engineers are Replacing Data Scientists

  Most Common SQL Mistakes on Data Science Interviews; Why Machine Learning Engineers are Replacing Data Scientists; Vote in new KDnuggets Poll: What Percentage of Your Machine Learning Models Have Been Deployed? KDnuggets: Personal History and Nuggets of Experience.

  https://www.kdnuggets.com/2021/n45.html

• Building Massively Scalable Machine Learning Pipelines with Microsoft Synapse ML

  The new platform provides a single API to abstract dozens of ML frameworks and databases.

  https://www.kdnuggets.com/2021/11/building-massively-scalable-machine-learning-pipelines-microsoft-synapse-ml.html

• Why Machine Learning Engineers are Replacing Data Scientists">Why Machine Learning Engineers are Replacing Data Scientists

  The hiring run for data scientists continues along at a strong clip around the world. But, there are other emerging roles that are demonstrating key value to organizations that you should consider based on your existing or desired skill sets.

  https://www.kdnuggets.com/2021/11/why-machine-learning-engineers-are-replacing-data-scientists.html

• 3 Differences Between Coding in Data Science and Machine Learning

  The terms ‘data science’ and ‘machine learning’ are often used interchangeably. But while they are related, there are some glaring differences, so let’s take a look at the differences between the two disciplines, specifically as it relates to programming.

  https://www.kdnuggets.com/2021/11/3-differences-coding-data-science-machine-learning.html

• Anecdotes from 11 Role Models in Machine Learning

  The skills needed to create good data are also the skills needed for good leadership.

  https://www.kdnuggets.com/2021/11/anecdotes-11-role-models-machine-learning.html

• The Common Misconceptions About Machine Learning

  Beginners in the field can often have many misconceptions about machine learning that sometimes can be a make-it-or-break-it moment for the individual switching careers or starting fresh. This article clearly describes the ground truth realities about learning new ML skills and eventually working professionally as a machine learning engineer.

  https://www.kdnuggets.com/2021/11/common-misconception-about-machine-learning.html

• Top Stories, Nov 1-7: What Google Recommends You do Before Taking Their Machine Learning or Data Science Course

  Also: Design Patterns for Machine Learning Pipelines; Data Scientist Career Path from Novice to First Job; Salary Breakdown of the Top Data Science Jobs; ORDAINED: The Python Project Template

  https://www.kdnuggets.com/2021/11/top-news-week-1101-1107.html

• Machine Learning Safety: Unsolved Problems

  There remain critical challenges in machine learning that, if left resolved, could lead to unintended consequences and unsafe use of AI in the future. As an important and active area of research, roadmaps are being developed to help guide continued ML research and use toward meaningful and robust applications.

  https://www.kdnuggets.com/2021/11/machine-learning-safety-unsolved-problems.html

• 7 of The Coolest Machine Learning Topics of 2021 at ODSC West

  At our upcoming event this November 16th-18th in San Francisco, ODSC West 2021 will feature a plethora of talks, workshops, and training sessions on machine learning topics, deep learning, NLP, MLOps, and so on. You can register now for 20% off all ticket types, or register for a free AI Expo Pass to see what some big names in AI are doing now.

  https://www.kdnuggets.com/2021/11/odsc-7-coolest-machine-learning-topics.html

• Design Patterns for Machine Learning Pipelines">Design Patterns for Machine Learning Pipelines

  ML pipeline design has undergone several evolutions in the past decade with advances in memory and processor performance, storage systems, and the increasing scale of data sets. We describe how these design patterns changed, what processes they went through, and their future direction.

  https://www.kdnuggets.com/2021/11/design-patterns-machine-learning-pipelines.html

• Top Stories, Oct 25-31: How I Tripled My Income With Data Science in 18 Months; Machine Learning Model Development and Model Operations: Principles and Practices

  Also: What Google Recommends You do Before Taking Their Machine Learning or Data Science Course; Learn To Reproduce Papers: Beginner’s Guide; 365 Data Science courses free until 18 November; A Guide to 14 Different Data Science Jobs

  https://www.kdnuggets.com/2021/11/top-news-week-1025-1031.html

• What Google Recommends You do Before Taking Their Machine Learning or Data Science Course">What Google Recommends You do Before Taking Their Machine Learning or Data Science Course

  First steps to learning data science & machine learning are the foundations.

  https://www.kdnuggets.com/2021/10/google-recommends-before-machine-learning-data-science-course.html

• Machine Learning Model Development and Model Operations: Principles and Practices">Machine Learning Model Development and Model Operations: Principles and Practices

  The ML model management and the delivery of highly performing model is as important as the initial build of the model by choosing right dataset. The concepts around model retraining, model versioning, model deployment and model monitoring are the basis for machine learning operations (MLOps) that helps the data science teams deliver highly performing models.

  https://www.kdnuggets.com/2021/10/machine-learning-model-development-operations-principles-practice.html

• How To Defeat The Machine Learning Engineer Impostor Syndrome

  How many times have you taken yet another online course on machine learning or read yet another paper on a new emerging topic, to be up-to-date in this crazy fast-paced AI/ML world -- only to keep feeling like an ML engineer impostor? These three personal tips can help you overcome the classic (and common) impostor syndrome behind every emerging ML engineer who wants to be better at what you do.

  https://www.kdnuggets.com/2021/10/defeat-machine-learning-engineer-impostor-syndrome.html

• KDnuggets™ News 21:n40, Oct 20: The 20 Python Packages You Need For Machine Learning and Data Science; Ace Data Science Interviews with Portfolio Projects

  The 20 Python Packages You Need For Machine Learning and Data Science; How to Ace Data Science Interview by Working on Portfolio Projects; Deploying Your First Machine Learning API; Real Time Image Segmentation Using 5 Lines of Code; What is Clustering and How Does it Work?

  https://www.kdnuggets.com/2021/n40.html

• Deploying Your First Machine Learning API">Deploying Your First Machine Learning API

  Effortless way to develop and deploy your machine learning API using FastAPI and Deta.

  https://www.kdnuggets.com/2021/10/deploying-first-machine-learning-api.html

• The 20 Python Packages You Need For Machine Learning and Data Science">The 20 Python Packages You Need For Machine Learning and Data Science

  Do you do Python? Do you do data science and machine learning? Then, you need to do these crucial Python libraries that enable nearly all you will want to do.

  https://www.kdnuggets.com/2021/10/20-python-packages.html

• Building Multimodal Models: Using the widedeep Pytorch package

  This article gets you started on the open-source widedeep PyTorch framework developed by Javier Rodriguez Zaurin.

  https://www.kdnuggets.com/2021/10/building-multimodal-models-widedeep-pytorch-package.html

• Here’s Why You Need Python Skills as a Machine Learning Engineer">Here’s Why You Need Python Skills as a Machine Learning Engineer

  If you want to learn how to apply Python programming skills in the context of AI applications, the UC San Diego Extension Machine Learning Engineering Bootcamp can help. Read on to find out more about how machine learning engineers use Python, and why the language dominates today’s machine learning landscape.

  https://www.kdnuggets.com/2021/10/bootcamp-python-skills-machine-learning-engineer.html

• The Architecture Behind DeepMind’s Model for Near Real Time Weather Forecasts

  Deep Generative Model of Rain (DGMR) is the newest creation from DeepMind which can predict precipitation in short term intervals.

  https://www.kdnuggets.com/2021/10/architecture-deepmind-model-near-real-time-weather-forecasts.html

• Cartoon: How Deep Is That Data Lake?

  New KDnuggets Cartoon looks at some of the problems data engineers may encounter when trying to measure data lakes.

  https://www.kdnuggets.com/2021/10/cartoon-data-lake.html

• KDnuggets™ News 21:n37, Sep 29: Nine Tools I Wish I Mastered Before My PhD in Machine Learning; Path to Full Stack Data Science

  Whether you have a PhD or not, learn these very useful 9 tools to increase your mastery of Machine Learning; Check this detailed path to becoming a full stack Data Scientist; Then do one of these 20 Machine Learning Projects that will help you get a job; See a Breakdown of Deep Learning Frameworks; and more.

  https://www.kdnuggets.com/2021/n37.html

• Top Stories, Sep 20-26: Nine Tools I Wish I Mastered Before My PhD in Machine Learning; How to Find Weaknesses in your Machine Learning Models

  Also: How to be a Data Scientist without a STEM degree; Data Scientists Without Data Engineering Skills Will Face the Harsh Truth; 20 Machine Learning Projects That Will Get You Hired; How to Find Weaknesses in your Machine Learning Models

  https://www.kdnuggets.com/2021/09/top-news-week-0920-0926.html

• 20 Machine Learning Projects That Will Get You Hired">20 Machine Learning Projects That Will Get You Hired

  If you want to break into the machine learning and data science job market, then you will need to demonstrate the proficiency of your skills, especially if you are self-taught through online courses and bootcamps. A project portfolio is a great way to practice your new craft and offer convincing evidence that an employee should hire you over the competition.

  https://www.kdnuggets.com/2021/09/20-machine-learning-projects-hired.html

• Nine Tools I Wish I Mastered Before My PhD in Machine Learning">Nine Tools I Wish I Mastered Before My PhD in Machine Learning

  Whether you are building a start up or making scientific breakthroughs these tools will bring your ML pipeline to the next level.

  https://www.kdnuggets.com/2021/09/nine-tools-mastered-before-phd-machine-learning.html

• How to Find Weaknesses in your Machine Learning Models">How to Find Weaknesses in your Machine Learning Models

  FreaAI: a new method from researchers at IBM.

  https://www.kdnuggets.com/2021/09/weaknesses-machine-learning-models.html

• Introduction to Automated Machine Learning

  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.

  https://www.kdnuggets.com/2021/09/introduction-automated-machine-learning.html

• KDnuggets™ News 21:n35, Sep 15: A Data Science Portfolio That Will Land You The Job; Top 18 Low-Code and No-Code Machine Learning Platforms

  Here is a Data Science Portfolio that will land you the job; Review the top 18 Low-Code and No-Code Machine Learning platforms; Try these 8 Deep Learning Project Ideas for Beginners; Very useful - working with Python APIs for data science project.

  https://www.kdnuggets.com/2021/n35.html

• An Introduction to Reinforcement Learning with OpenAI Gym, RLlib, and Google Colab

  Get an Introduction to Reinforcement Learning by attempting to balance a virtual CartPole with OpenAI Gym, RLlib, and Google Colab.

  https://www.kdnuggets.com/2021/09/intro-reinforcement-learning-openai-gym-rllib-colab.html

• Top 18 Low-Code and No-Code Machine Learning Platforms">Top 18 Low-Code and No-Code Machine Learning Platforms

  Machine learning becomes more accessible to companies and individuals when there is less coding involved. Especially if you are just starting your path in ML, then check out these low-code and no-code platforms to help expedite your capabilities in learning and applying AI.

  https://www.kdnuggets.com/2021/09/top-18-low-code-no-code-machine-learning-platforms.html

• Math 2.0: The Fundamental Importance of Machine Learning

  Machine learning is not just another way to program computers; it represents a fundamental shift in the way we understand the world. It is Math 2.0.

  https://www.kdnuggets.com/2021/09/math-fundamental-importance-machine-learning.html

• How Machine Learning Leverages Linear Algebra to Solve Data Problems

  Why you should learn the fundamentals of linear algebra.

  https://www.kdnuggets.com/2021/09/machine-learning-leverages-linear-algebra-solve-data-problems.html

• Antifragility and Machine Learning

  Our intuition for most products, processes, and even some models might be that they either will get worse over time, or if they fail, they will experience an cascade of more failure. But, what if we could intentionally design systems and models to only get better, even as the world around them gets worse?

  https://www.kdnuggets.com/2021/09/antifragility-machine-learning.html

• How to solve machine learning problems in the real world

  Becoming a machine learning engineer pro is your goal? Sure, online ML courses and Kaggle-style competitions are great resources to learn the basics. However, the daily job of a ML engineer requires an additional layer of skills that you won’t master through these approaches.

  https://www.kdnuggets.com/2021/09/solve-machine-learning-problems-real-world.html

• Learning Data Science and Machine Learning: First Steps After The Roadmap">Learning Data Science and Machine Learning: First Steps After The Roadmap

  Just getting into learning data science may seem as daunting as (if not more than) trying to land your first job in the field. With so many options and resources online and in traditional academia to consider, these pre-requisites and pre-work are recommended before diving deep into data science and AI/ML.

  https://www.kdnuggets.com/2021/08/learn-data-science-machine-learning.html

• KDnuggets™ News 21:n31, Aug 18: The Difference Between Data Scientists and ML Engineers; MLOPs And Machine Learning RoadMap

  What is the difference between Data Scientists and ML Engineers? How does MLOPs fit into Machine Learning RoadMap? How to Train a BERT Model From Scratch? What is so great about Intro to Statistical Learning, 2nd Edition? Find the answers to these questions and more in this issue.

  https://www.kdnuggets.com/2021/n31.html

• Model Drift in Machine Learning – How To Handle It In Big Data

  Rendezvous Architecture helps you run and choose outputs from a Champion model and many Challenger models running in parallel without many overheads. The original approach works well for smaller data sets, so how can this idea adapt to big data pipelines?

  https://www.kdnuggets.com/2021/08/model-drift-machine-learning-big-data.html

• Introduction to Statistical Learning Second Edition

  The second edition of the classic "An Introduction to Statistical Learning, with Applications in R" was published very recently, and is now freely-available via PDF on the book's website.

  https://www.kdnuggets.com/2021/08/introduction-statistical-learning-v2.html

• DeepMind’s New Super Model: Perceiver IO is a Transformer that can Handle Any Dataset

  The new transformer-based architecture can process audio, video and images using a single model.

  https://www.kdnuggets.com/2021/08/deepmind-new-super-model-perceiver-io-transformer.html

• How DeepMind Trains Agents to Play Any Game Without Intervention

  A new paper proposes a new architecture and training environment for generally capable agents.

  https://www.kdnuggets.com/2021/08/deepmind-trains-agents-play-without-intervention.html

• 10 Machine Learning Model Training Mistakes

  These common ML model training mistakes are easy to overlook but costly to redeem.

  https://www.kdnuggets.com/2021/07/10-machine-learning-model-training-mistakes.html

• Building Machine Learning Pipelines using Snowflake and Dask

  In this post, I want to share some of the tools that I have been exploring recently and show you how I use them and how they helped improve the efficiency of my workflow. The two I will talk about in particular are Snowflake and Dask. Two very different tools but ones that complement each other well especially as part of the ML Lifecycle.

  https://www.kdnuggets.com/2021/07/building-machine-learning-pipelines-snowflake-dask.html

• KDnuggets™ News 21:n28, Jul 28: Design patterns in machine learning; The Best NLP Course is Free

  What are the Design patterns for Machine Learning and why you should know them? For more advanced readers, how to use Kafka Connect to create an open source data pipeline for processing real-time data; The state-of-the-art NLP course is freely available; Python Data Structures Compared; Update your Machine Learning skills this summer.

  https://www.kdnuggets.com/2021/n28.html

• Machine Learning Skills – Update Yours This Summer

  The process of mastering new knowledge often requires multiple passes to ensure the information is deeply understood. If you already began your journey into machine learning and data science, then you are likely ready for a refresher on topics you previously covered. This eight-week self-learning path will help you recapture the foundations and prepare you for future success in applying these skills.

  https://www.kdnuggets.com/2021/07/update-your-machine-learning-skills.html

• Design patterns in machine learning">Design patterns in machine learning

  Can we abstract best practices to real design patterns yet?

  https://www.kdnuggets.com/2021/07/design-patterns-machine-learning.html

• How Much Memory is your Machine Learning Code Consuming?

  Learn how to quickly check the memory footprint of your machine learning function/module with one line of command. Generate a nice report too.

  https://www.kdnuggets.com/2021/07/memory-machine-learning-code-consuming.html

• How to Create Unbiased Machine Learning Models

  In this post we discuss the concepts of bias and fairness in the Machine Learning world, and show how ML biases often reflect existing biases in society. Additionally, We discuss various methods for testing and enforcing fairness in ML models.

  https://www.kdnuggets.com/2021/07/create-unbiased-machine-learning-models.html

• Pushing No-Code Machine Learning to the Edge

  Discover the power of no-code machine learning, and what it can accomplish when pushed to edge devices.

  https://www.kdnuggets.com/2021/07/pushing-no-code-machine-learning-edge.html

• A Learning Path To Becoming a Data Scientist">A Learning Path To Becoming a Data Scientist

  Becoming a professional data scientist may not be as easy as "1... 2... 3...", but these 10 steps can be your self-learning roadmap to kickstarting your future in the exciting and ever-expanding field of data science.

  https://www.kdnuggets.com/2021/07/learning-path-data-scientist.html

• Learning Data Science Through Social Media

  Want your social media algorithms to show you actual algorithms? Spare a moment during your social media scrolling to learn a bit of data science. Here are suggestions for at-a-glance access to good ideas and tips on your favorite platforms.

  https://www.kdnuggets.com/2021/07/learning-data-science-through-social-media.html

• Amazing Low-Code Machine Learning Capabilities with New Ludwig Update

  Integration with Ray, MLflow and TabNet are among the top features of this release.

  https://www.kdnuggets.com/2021/06/ludwig-update-includes-low-code-machine-learning-capabilities.html

• Dashboards for Interpreting & Comparing Machine Learning Models

  This article discusses using Interpret to create dashboards for machine learning models.

  https://www.kdnuggets.com/2021/06/dashboards-interpreting-comparing-machine-learning-models.html

• Facebook Launches One of the Toughest Reinforcement Learning Challenges in History

  The FAIR team just launched the NetHack Challenge as part of the upcoming NeurIPS 2021 competition. The objective is to test new RL ideas using a one of the toughest game environments in the world.

  https://www.kdnuggets.com/2021/06/facebook-launches-toughest-reinforcement-learning-challenges.html

• 9 Deadly Sins of Machine Learning Dataset Selection

  Avoid endless pain in model debugging by focusing on datasets upfront.

  https://www.kdnuggets.com/2021/06/9-deadly-sins-ml-dataset-selection.html

• KDnuggets™ News 21:n21, Jun 9: 5 Tasks To Automate With Python; How I Doubled My Income with Data Science and Machine Learning

  5 Tasks To Automate With Python; How I Doubled My Income with Data Science and Machine Learning; Will There Be a Shortage of Data Science Jobs in the Next 5 Years?; How to Make Python Code Run Incredibly Fast; Stop (and Start) Hiring Data Scientists

  https://www.kdnuggets.com/2021/n21.html

• Top Stories, May 31 – Jun 6: A Guide On How To Become A Data Scientist (Step By Step Approach); How I Doubled My Income with Data Science and Machine Learning

  Also: 5 Tasks To Automate With Python; How I Doubled My Income with Data Science and Machine Learning; Will There Be a Shortage of Data Science Jobs in the Next 5 Years?; How to Make Python Code Run Incredibly Fast

  https://www.kdnuggets.com/2021/06/top-news-week-0531-0606.html

• 10 Deadly Sins of Machine Learning Model Training

  These mistakes are easy to overlook but costly to redeem.

  https://www.kdnuggets.com/2021/06/10-deadly-sins-machine-learning-model-training.html

• Machine Learning Model Interpretation

  Read this overview of using Skater to build machine learning visualizations.

  https://www.kdnuggets.com/2021/06/machine-learning-model-interpretation.html

• Data Validation in Machine Learning is Imperative, Not Optional

  Before we reach model training in the pipeline, there are various components like data ingestion, data versioning, data validation, and data pre-processing that need to be executed. In this article, we will discuss data validation, why it is important, its challenges, and more.

  https://www.kdnuggets.com/2021/05/data-validation-machine-learning-imperative.html

• How to Determine if Your Machine Learning Model is Overtrained">How to Determine if Your Machine Learning Model is Overtrained

  WeightWatcher is based on theoretical research (done injoint with UC Berkeley) into Why Deep Learning Works, based on our Theory of Heavy Tailed Self-Regularization (HT-SR). It uses ideas from Random Matrix Theory (RMT), Statistical Mechanics, and Strongly Correlated Systems.

  https://www.kdnuggets.com/2021/05/how-determine-machine-learning-model-overtrained.html

• Top Stories, May 10-16: Essential Linear Algebra for Data Science and Machine Learning

  Also: Data Preparation in SQL, with Cheat Sheet!; Best Python Books for Beginners and Advanced Programmers; Similarity Metrics in NLP; The NoSQL Know-It-All Compendium

  https://www.kdnuggets.com/2021/05/top-news-week-0510-0516.html

• Binary Classification with Automated Machine Learning

  Check out how to use the open-source MLJAR auto-ML to build accurate models faster.

  https://www.kdnuggets.com/2021/05/binary-classification-automated-machine-learning.html

• What makes a winning entry in a Machine Learning competition?

  So you want to show your grit in a Kaggle-style competition? Many, many others have the same idea, including domain experts and non-experts, and academic and corporate teams. What does it take for your bright ideas and skills to come out on top of thousands of competitors?

  https://www.kdnuggets.com/2021/05/winning-machine-learning-competition.html

• The Machine Learning Research Championed by the Biggest AI Labs in the World

  How Google, Microsoft, Facebook, DeepMind, OpenAI, Amazon and IBM think about the future of AI.

  https://www.kdnuggets.com/2021/05/machine-learning-research-biggest-ai-labs.html

• Top Stories, Apr 26 – May 2: Data Scientist vs Machine Learning Engineer – what are their skills?

  Also: Data Science Books You Should Start Reading in 2021; Data science is not about data – applying Dijkstra principle to data science; How to ace A/B Testing Data Science Interviews; Top 10 Must-Know Machine Learning Algorithms for Data Scientists – Part 1

  https://www.kdnuggets.com/2021/05/top-news-week-0426-0502.html

• Best Podcasts for Machine Learning

  Podcasts, especially those featuring interviews, are great for learning about the subfields and tools of AI, as well as the rock stars and superheroes of the AI world. Here, we highlight some of the best podcasts today that are perfect for both those learning about machine learning and seasoned practitioners.

  https://www.kdnuggets.com/2021/04/best-podcasts-machine-learning.html

• Data Scientist vs Machine Learning Engineer – what are their skills?">Data Scientist vs Machine Learning Engineer – what are their skills?

  As two very popular tech roles for 2021, the Data Scientist and Machine Learning Engineer can overlap or be entirely distinct, depending on the organization you work for. However, general differences between these positions require certain skill sets that you must be prepared for when applying for jobs.

  https://www.kdnuggets.com/2021/04/data-scientist-machine-learning-engineer-skills.html

• How Uber manages Machine Learning Experiments with Comet.ml

  At Uber, where ML is fundamental to most products, a mechanism to manage offline experiments easily is needed to improve developer velocity. To solve for this, Uber AI was looking for a solution that will potentially complement and extend its in-house experiment management and collaboration capabilities.

  https://www.kdnuggets.com/2021/04/comet-uber-machine-learning-experiments.html

• Free From Stanford: Machine Learning with Graphs

  Check out the freely-available Stanford course Machine Learning with Graphs, taught by Jure Leskovec, and see how a world renowned researcher teaches their topic of expertise. Accessible materials include slides, videos, and more.

  https://www.kdnuggets.com/2021/04/free-stanford-machine-learning-graphs.html

• 6 Mistakes To Avoid While Training Your Machine Learning Model

  While training the AI model, multi-stage activities are performed to utilize the training data in the best manner, so that outcomes are satisfying. So, here are the 6 common mistakes you need to understand to make sure your AI model is successful.

  https://www.kdnuggets.com/2021/04/cogitotech-6-mistakes-avoid-training-machine-learning.html

• KDnuggets™ News 21:n14, Apr 14: A/B Testing: Common Questions and Answers in Data Science Interviews; Interpretable Machine Learning: The Free eBook

  Common Questions and Answers on A/B testing in Data Science Interviews; Interpretable Machine Learning: The Free eBook; Why machine learning struggles with causality; Deep Learning Recommendation Models: A Deep Dive; and more.

  https://www.kdnuggets.com/2021/n14.html

• 10 Real-Life Applications of Reinforcement Learning

  In this article, we’ll look at some of the real-world applications of reinforcement learning.

  https://www.kdnuggets.com/2021/04/10-real-life-applications-reinforcement-learning.html

• Zero-Shot Learning: Can you classify an object without seeing it before?

  Developing machine learning models that can perform predictive functions on data it has never seen before has become an important research area called zero-shot learning. We tend to be pretty great at recognizing things in the world we never saw before, and zero-shot learning offers a possible path toward mimicking this powerful human capability.

  https://www.kdnuggets.com/2021/04/zero-shot-learning.html

• Deepfakes are now mainstream. What’s next?

  Deepfakes have become mainstream. Here we take a closer look at recent news about deepfakes, and what it all might mean for the future.

  https://www.kdnuggets.com/2021/04/deepfakes-mainstream-next.html

• Why machine learning struggles with causality

  If there's one thing people know how to do, and that's guess what caused something else to happen. Usually these guesses are good, especially when making a visual observation of something in the physical world. AI continues to wrestle with such inference of causality, and fundamental challenges must be overcome before we can have "intuitive" machine learning.

  https://www.kdnuggets.com/2021/04/machine-learning-struggles-causality.html

• KDnuggets™ News 21:n13, Apr 7: Top 10 Python Libraries Data Scientists should know in 2021; KDnuggets Top Blogs Reward Program; Making Machine Learning Models Understandable

  Top 10 Python Libraries Data Scientists should know in 2021; KDnuggets Top Blogs Reward Program; Shapash: Making Machine Learning Models Understandable; Easy AutoML in Python; The 8 Most Common Data Scientists; A/B Testing: 7 Common Questions and Answers in Data Science Interviews, Part 1

  https://www.kdnuggets.com/2021/n13.html

• Top Stories, Mar 29 – Apr 4: Top 10 Python Libraries Data Scientists should know in 2021; Shapash: Making Machine Learning Models Understandable

  Also: The 8 Most Common Data Scientists; Easy AutoML in Python; How to Succeed in Becoming a Freelance Data Scientist; The 8 Most Common Data Scientists

  https://www.kdnuggets.com/2021/04/top-news-week-0329-0404.html

• The Best Machine Learning Frameworks & Extensions for TensorFlow

  Check out this curated list of useful frameworks and extensions for TensorFlow.

  https://www.kdnuggets.com/2021/04/best-machine-learning-frameworks-extensions-tensorflow.html

• Shapash: Making Machine Learning Models Understandable">Shapash: Making Machine Learning Models Understandable

  Establishing an expectation for trust around AI technologies may soon become one of the most important skills provided by Data Scientists. Significant research investments are underway in this area, and new tools are being developed, such as Shapash, an open-source Python library that helps Data Scientists make machine learning models more transparent and understandable.

  https://www.kdnuggets.com/2021/04/shapash-machine-learning-models-understandable.html

• Top YouTube Machine Learning Channels

  These are the top 15 YouTube channels for machine learning as determined by our stated criteria, along with some additional data on the channels to help you decide if they may have some content useful for you.

  https://www.kdnuggets.com/2021/03/top-youtube-machine-learning-channels.html

• The Best Machine Learning Frameworks & Extensions for Scikit-learn">The Best Machine Learning Frameworks & Extensions for Scikit-learn

  Learn how to use a selection of packages to extend the functionality of Scikit-learn estimators.

  https://www.kdnuggets.com/2021/03/best-machine-learning-frameworks-extensions-scikit-learn.html

• Learning from machine learning mistakes

  Read this article and discover how to find weak spots of a regression model.

  https://www.kdnuggets.com/2021/03/learning-from-machine-learning-mistakes.html

• Automating Machine Learning Model Optimization

  This articles presents an overview of using Bayesian Tuning and Bandits for machine learning.

  https://www.kdnuggets.com/2021/03/automating-machine-learning-model-optimization.html

• 10 Amazing Machine Learning Projects of 2020">10 Amazing Machine Learning Projects of 2020

  So much progress in AI and machine learning happened in 2020, especially in the areas of AI-generating creativity and low-to-no-code frameworks. Check out these trending and popular machine learning projects released last year, and let them inspire your work throughout 2021.

  https://www.kdnuggets.com/2021/03/10-amazing-machine-learning-projects-2020.html

• DeepMind’s AlphaFold & the Protein Folding Problem

  Recently, DeepMind's AlphaFold made impressive headway in the protein structure prediction problem. Read this for an overview and explanation.

  https://www.kdnuggets.com/2021/03/deepmind-alphafold-protein-folding-problem.html

• Getting Started with Distributed Machine Learning with PyTorch and Ray

  Ray is a popular framework for distributed Python that can be paired with PyTorch to rapidly scale machine learning applications.

  https://www.kdnuggets.com/2021/03/getting-started-distributed-machine-learning-pytorch-ray.html

• Top Stories, Feb 22-28: We Don’t Need Data Scientists, We Need Data Engineers; Data Science Learning Roadmap for 2021

  Also: Powerful Exploratory Data Analysis in just two lines of code; Machine Learning Systems Design: A Free Stanford Course; Telling a Great Data Story: A Visualization Decision Tree

  https://www.kdnuggets.com/2021/03/top-news-week-0222-0228.html

• Data Science Learning Roadmap for 2021">Data Science Learning Roadmap for 2021

  Venturing into the world of Data Science is an exciting, interesting, and rewarding path to consider. There is a great deal to master, and this self-learning recommendation plan will guide you toward establishing a solid understanding of all that is foundational to data science as well as a solid portfolio to showcase your developed expertise.

  https://www.kdnuggets.com/2021/02/data-science-learning-roadmap-2021.html

• Machine Learning Systems Design: A Free Stanford Course">Machine Learning Systems Design: A Free Stanford Course

  This freely-available course from Stanford should give you a toolkit for designing machine learning systems.

  https://www.kdnuggets.com/2021/02/machine-learning-systems-design-free-stanford-course.html

• Why Do Machine Learning Projects Fail?

  At the beginning of any data science project, many challenges could arise that lead to its eventual collapse. Making sure you look ahead -- early in the planning -- toward putting your resulting model into production can help increase the chance of delivering long-term value with your developed machine learning system.

  https://www.kdnuggets.com/2021/02/why-machine-learning-projects-fail.html

• Approaching (Almost) Any Machine Learning Problem">Approaching (Almost) Any Machine Learning Problem

  This freely-available book is a fantastic walkthrough of practical approaches to machine learning problems.

  https://www.kdnuggets.com/2021/02/approaching-almost-any-machine-learning-problem.html

• IBM Uses Continual Learning to Avoid The Amnesia Problem in Neural Networks

  Using continual learning might avoid the famous catastrophic forgetting problem in neural networks.

  https://www.kdnuggets.com/2021/02/ibm-continual-learning-avoid-amnesia-problem-neural-networks.html

• Machine Learning – it’s all about assumptions

  Just as with most things in life, assumptions can directly lead to success or failure. Similarly in machine learning, appreciating the assumed logic behind machine learning techniques will guide you toward applying the best tool for the data.

  https://www.kdnuggets.com/2021/02/machine-learning-assumptions.html

• A Critical Comparison of Machine Learning Platforms in an Evolving Market

  There’s a clear inclination towards the MLaaS model across industries, given the fact that companies today have an option to select from a wide range of solutions that can cater to diverse business needs. Here is a look at 3 of the top ML platforms for data excellence.

  https://www.kdnuggets.com/2021/02/critical-comparison-machine-learning-platforms-evolving-market.html

• My machine learning model does not learn. What should I do?

  This article presents 7 hints on how to get out of the quicksand.

  https://www.kdnuggets.com/2021/02/machine-learning-model-not-learn.html

• Microsoft Explores Three Key Mysteries of Ensemble Learning

  A new paper studies three key puzzling characteristics of deep learning ensembles and some potential explanations.

  https://www.kdnuggets.com/2021/02/microsoft-explores-three-key-mysteries-ensemble-learning.html

• 2011: DanNet triggers deep CNN revolution

  In 2021, we are celebrating the 10-year anniversary of DanNet, which, in 2011, was the first pure deep convolutional neural network (CNN) to win computer vision contests. Read about its history here.

  https://www.kdnuggets.com/2021/02/dannet-triggers-deep-cnn-revolution.html

• Past 2021 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-2021.html

• KDnuggets™ News 21:n05, Feb 3: How to Get a Job as a Data Scientist; Popular Machine Learning Interview Questions, part 2

  Learn how to get a job as Data Scientist; it will help if you study popular machine learning interview questions; Beyond the Nash Equilibrium: DeepMind Clever Strategy to Solve Asymmetric Games; Understanding Bayes Theorem; and more.

  https://www.kdnuggets.com/2021/n05.html

• Top Stories, Jan 25-31: Want to Be a Data Scientist? Don’t Start With Machine Learning; The Ultimate Scikit-Learn Machine Learning Cheatsheet

  Also: How I Got 4 Data Science Offers and Doubled my Income 2 Months After Being Laid Off; How to Get a Job as a Data Scientist; Data Engineering — the Cousin of Data Science, is Troublesome; What to Learn to Become a Data Scientist in 2021

  https://www.kdnuggets.com/2021/02/top-news-week-0125-0131.html

• Beyond the Nash Equilibrium: DeepMind Clever Strategy to Solve Asymmetric Games

  The method expands the concept of a Nash equilibrium by decomposing an asymmetric game into multiple symmetric games.

  https://www.kdnuggets.com/2021/02/beyond-nash-equilibrium-deepmind-solve-asymmetric-games.html

• Machine learning adversarial attacks are a ticking time bomb

  Software developers and cyber security experts have long fought the good fight against vulnerabilities in code to defend against hackers. A new, subtle approach to maliciously targeting machine learning models has been a recent hot topic in research, but its statistical nature makes it difficult to find and patch these so-called adversarial attacks. Such threats in the real-world are becoming imminent as the adoption of machine learning spreads, and a systematic defense must be implemented.

  https://www.kdnuggets.com/2021/01/machine-learning-adversarial-attacks.html

• Top 5 Reasons Why Machine Learning Projects Fail

  The rise in machine learning project implementation is coming, as is the the number of failures, due to several implementation and maintenance challenges. The first step of closing this gap lies in understanding the reasons for the failure.

  https://www.kdnuggets.com/2021/01/top-5-reasons-why-machine-learning-projects-fail.html

• Machine learning is going real-time

  Extracting immediate predictions from machine learning algorithms on the spot based on brand-new data can offer a next level of interaction and potential value to its consumers. The infrastructure and tech stack required to implement such real-time systems is also next level, and many organizations -- especially in the US -- seem to be resisting. But, what even is real-time ML, and how can it deliver a better experience?

  https://www.kdnuggets.com/2021/01/machine-learning-real-time.html

• Popular Machine Learning Interview Questions, part 2

  Get ready for your next job interview requiring domain knowledge in machine learning with answers to these thirteen common questions.

  https://www.kdnuggets.com/2021/01/popular-machine-learning-interview-questions-part2.html

• Want to Be a Data Scientist? Don’t Start With Machine Learning">Want to Be a Data Scientist? Don’t Start With Machine Learning

  Machine learning may appear like the go-to topic to start learning for the aspiring data scientist. But. thinking these techniques are the key aspects of the role is the biggest misconception. So much more goes into becoming a successful data scientist, and machine learning is only one component of broader skills around processing, managing, and understanding the science behind the data.

  https://www.kdnuggets.com/2021/01/data-scientist-dont-start-machine-learning.html

• Going Beyond the Repo: GitHub for Career Growth in AI & Machine Learning

  Many online tools and platforms exist to help you establish a clear and persuasive online profile for potential employers to review. Have you considered how your go-to online code repository could also help you land your next job?

  https://www.kdnuggets.com/2021/01/github-career-growth-ai-machine-learning.html

• Popular Machine Learning Interview Questions">Popular Machine Learning Interview Questions

  Get ready for your next job interview requiring domain knowledge in machine learning with answers to these eleven common questions.

  https://www.kdnuggets.com/2021/01/popular-machine-learning-interview-questions.html