Search results for Reinforcement Learning

Found 411 documents, 5944 searched:

• ChatGPT for Beginners

  List of best crash courses for ChatGPT.

  https://www.kdnuggets.com/2023/02/chatgpt-beginners.html

• 5 Free Data Science Books You Must Read in 2023

  Get your hands on these gems to learn Python, data analytics, machine learning, and deep learning.

  https://www.kdnuggets.com/2023/01/5-free-data-science-books-must-read-2023.html

• ChatGPT: Everything You Need to Know

  All you need to know about ChatGPT: what it can do, how it works, and its limitations.

  https://www.kdnuggets.com/2023/01/chatgpt-everything-need-know.html

• 3 Things I Wish I Knew When I Started Data Science

  Looking back and realizing how I was wrong about the data science career.

  https://www.kdnuggets.com/2023/01/3-things-wish-knew-started-data-science.html

• Master Transformers with This Free Stanford Course!

  If you want a deep dive on transformers, this Stanford course has made its courseware freely available, including lecture videos, readings, assignments, and more.

  https://www.kdnuggets.com/2022/09/master-transformers-free-stanford-course.html

• The Complete Collection of Data Science Projects – Part 2

  The second part covers the list of Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, Data Engineering, and MLOps.

  https://www.kdnuggets.com/2022/08/complete-collection-data-science-projects-part-2.html

• Online Training and Workshops with Nvidia

  Learn about the Nvidia Self-Paced Online Training from their Deep Learning Institute.

  https://www.kdnuggets.com/2022/07/online-training-workshops-nvidia.html

• Understanding Agent Environment in AI

  The role of the agent is always very important in artificial intelligence, machine learning, and deep learning. Learn more about agents here.

  https://www.kdnuggets.com/2022/05/understanding-agent-environment-ai.html

• Quick Data Science Tips and Tricks to Learn SAS

  How To Tutorials with SAS data scientists and analytics instructors.

  https://www.kdnuggets.com/2022/05/sas-quick-data-science-tips-tricks-learn.html

• Python Libraries Data Scientists Should Know in 2022

  Let’s have a look at the Python libraries that every data scientist should know in 2022, to maintain and improve their coding journey.

  https://www.kdnuggets.com/2022/04/python-libraries-data-scientists-know-2022.html

• Uncertainty Quantification in Artificial Intelligence-based Systems

  The article summarizes the plethora of UQ methods using Bayesian techniques, shows issues and gaps in the literature, suggests further directions, and epitomizes AI-based systems within the Financial Crime domain.

  https://www.kdnuggets.com/2022/04/uncertainty-quantification-artificial-intelligencebased-systems.html

• 8 Free MIT Courses to Learn Data Science Online

  Create a data science learning path with courses from the world’s most prestigious university.

  https://www.kdnuggets.com/2022/03/8-free-mit-courses-learn-data-science-online.html

• The Most Popular Intro to Programming Course From Harvard is Free!

  CS50's Introduction to Computer Science has the highest enrollment on Harvard's campus... and is free to anyone interested in taking it!

  https://www.kdnuggets.com/2022/03/popular-intro-programming-course-harvard-free.html

• How a Level System can Help Forecast AI Costs

  To forecast costs for AI systems, it can be useful to talk about their “level” just like SAE has levels for self-driving cars. Adopting a level system can help organizations plan and prepare for AI systems that scale in complexity over time.

  https://www.kdnuggets.com/2022/03/level-system-help-forecast-ai-costs.html

• KDnuggets™ News 22:n01, Jan 5: 3 Tools to Track and Visualize the Execution of Your Python Code; 6 Predictive Models Every Beginner Data Scientist Should Master

  3 Tools to Track and Visualize the Execution of Your Python Code; 6 Predictive Models Every Beginner Data Scientist Should Master; What Makes Python An Ideal Programming Language For Startups; Alternative Feature Selection Methods in Machine Learning; Explainable Forecasting and Nowcasting with State-of-the-art Deep Neural Networks and Dynamic Factor Model

  https://www.kdnuggets.com/2022/n01.html

• Should You Become a Freelance Artificial Intelligence Engineer?

  Take the first step towards your machine learning engineering career and explore the UC San Diego Extension Machine Learning Engineering Bootcamp today. Those with prior software engineering or data science experience are encouraged to apply.

  https://www.kdnuggets.com/2021/12/ucsd-become-freelance-artificial-intelligence-engineer.html

• KDnuggets: Personal History and Nuggets of Experience

  After 28+ years of publishing and editing KDnuggets, I am retiring and transitioning KDnuggets to Matthew Mayo, who will become the new editor-in-chief. I want to share with you my story of KDnuggets and highlight some of the useful nuggets of experience I learned along this amazing journey.

  https://www.kdnuggets.com/2021/11/kdnuggets-history.html

• 25 Github Repositories Every Python Developer Should Know

  Check out these repositories to help you improve your data science skills.

  https://www.kdnuggets.com/2021/11/25-github-repositories-python-developer.html

• Serving ML Models in Production: Common Patterns

  Over the past couple years, we've seen 4 common patterns of machine learning in production: pipeline, ensemble, business logic, and online learning. In the ML serving space, implementing these patterns typically involves a tradeoff between ease of development and production readiness. Ray Serve was built to support these patterns by being both easy to develop and production ready.

  https://www.kdnuggets.com/2021/10/serving-ml-models-production-common-patterns.html

• Scaling human oversight of AI systems for difficult tasks – OpenAI approach

  The foundational idea of Artificial Intelligence is that it should demonstrate human-level intelligence. So, unless a model can perform as a human might do, its intended purpose is missed. Here, recent OpenAI research into full-length book summarization focuses on generating results that make sense to humans with state-of-the-art results that leverage scalable AI-enhanced human-in-the-loop feedback.

  https://www.kdnuggets.com/2021/10/openai-scaling-human-oversight-ai-systems.html

• Path to Full Stack Data Science">Path to Full Stack Data Science

  Start your journey toward mastering all aspects of the field of Data Science with this focused list of in-depth self-learning resources. Curated with the beginner in mind, these recommendations will help you learn efficiently, and can also offer existing professionals useful highlights for review or help filling in any gaps in skills.

  https://www.kdnuggets.com/2021/09/path-full-stack-data-science.html

• Data Science Cheat Sheet 2.0">Data Science Cheat Sheet 2.0

  Check out this helpful, 5-page data science cheat sheet to assist with your exam reviews, interview prep, and anything in-between.

  https://www.kdnuggets.com/2021/09/data-science-cheat-sheet.html

• Linear Algebra for Natural Language Processing

  Learn about representing word semantics in vector space.

  https://www.kdnuggets.com/2021/08/linear-algebra-natural-language-processing.html

• Visualizing Bias-Variance

  In this article, we'll explore some different perspectives of what the bias-variance trade-off really means with the help of visualizations.

  https://www.kdnuggets.com/2021/08/visualizing-bias-variance.html

• ARTIFICIAL INTELLIGENCE (AI), A TEXTBOOK

  This book covers the broader field of AI, carefully balancing coverage between classical AI (logic or deductive reasoning) and modern AI (inductive learning and neural networks).

  https://www.kdnuggets.com/2021/07/charu-ai-textbook.html

• Facebook Open Sources a Chatbot That Can Discuss Any Topic

  The new version expands the capabilities of its predecessor building a much more natural conversational experience.

  https://www.kdnuggets.com/2021/07/facebook-open-sources-chatbot-discuss-any-topic.html

• A Graph-based Text Similarity Method with Named Entity Information in NLP

  In this article, the author summarizes the 2017 paper "A Graph-based Text Similarity Measure That Employs Named Entity Information" as per their understanding. Better understand the concepts by reading along.

  https://www.kdnuggets.com/2021/06/graph-based-text-similarity-method-named-entity-information-nlp.html

• Five types of thinking for a high performing data scientist"> Five types of thinking for a high performing data scientist

  The way you think about a problem and the conceptual process you go through to find a solution may be guided by your personal skills or the type of problem at hand. Many mental models exist representing a variety of thinking patterns -- and as a Data Scientist, appreciating different approaches can help you more effectively model data in the business world and communicate your results to the decision-makers.

  https://www.kdnuggets.com/2021/06/five-types-thinking-data-scientist.html

• The 7 Best Open Source AI Libraries You May Not Have Heard Of

  AI researchers today have many exciting options for working with specialized tools. Although starting original projects from scratch is often not necessary, knowing which existing library to leverage remains a challenge. This list of generally unknown yet awesome, open-source libraries offers an interesting collection to consider for state-of-the-art research that spans from automatic machine learning to differentiable quantum circuits.

  https://www.kdnuggets.com/2021/06/7-open-source-ai-libraries.html

• Will There Be a Shortage of Data Science Jobs in the Next 5 Years?">Will There Be a Shortage of Data Science Jobs in the Next 5 Years?

  The data science workflow is getting automated day by day.

  https://www.kdnuggets.com/2021/06/shortage-data-science-jobs-5-years.html

• A checklist to track your Data Science progress">A checklist to track your Data Science progress

  Whether you are just starting out in data science or already a gainfully-employed professional, always learning more to advance through state-of-the-art techniques is part of the adventure. But, it can be challenging to track of your progress and keep an eye on what's next. Follow this checklist to help you scale your expertise from entry-level to advanced.

  https://www.kdnuggets.com/2021/05/checklist-data-science-progress.html

• How to Speed Up Pandas with Modin

  The Modin library has the ability to scale your pandas workflows by changing one line of code and integration with the Python ecosystem and Ray clusters. This tutorial goes over how to get started with Modin and how it can speed up your pandas workflows.

  https://www.kdnuggets.com/2021/03/speed-up-pandas-modin.html

• Google’s Model Search is a New Open Source Framework that Uses Neural Networks to Build Neural Networks">Google’s Model Search is a New Open Source Framework that Uses Neural Networks to Build Neural Networks

  The new framework brings state-of-the-art neural architecture search methods to TensorFlow.

  https://www.kdnuggets.com/2021/03/google-model-search-open-source-framework.html

• How Reading Papers Helps You Be a More Effective Data Scientist"> How Reading Papers Helps You Be a More Effective Data Scientist

  By reading papers, we were able to learn what others (e.g., LinkedIn) have found to work (and not work). We can then adapt their approach and not have to reinvent the rocket. This helps us deliver a working solution with lesser time and effort.

  https://www.kdnuggets.com/2021/02/reading-papers-effective-data-scientist.html

• 11 Industrial AI Trends that will Dominate the World in 2021

  These trends broadly cover the three themes of: Where will businesses adopt AI in 2021? How will AI become more accessible? How will AI capabilities evolve?

  https://www.kdnuggets.com/2021/01/11-industrial-ai-trends-dominate-2021.html

• 20 Core Data Science Concepts for Beginners">20 Core Data Science Concepts for Beginners

  With so much to learn and so many advancements to follow in the field of data science, there are a core set of foundational concepts that remain essential. Twenty of these ideas are highlighted here that are key to review when preparing for a job interview or just to refresh your appreciation of the basics.

  https://www.kdnuggets.com/2020/12/20-core-data-science-concepts-beginners.html

• Remembering Pluribus: The Techniques that Facebook Used to Master World’s Most Difficult Poker Game

  Pluribus used incredibly simple AI methods to set new records in six-player no-limit Texas Hold’em poker. How did it do it?

  https://www.kdnuggets.com/2020/12/remembering-pluribus-facebook-master-difficult-poker-game.html

• A Friendly Introduction to Graph Neural Networks

  Despite being what can be a confusing topic, graph neural networks can be distilled into just a handful of simple concepts. Read on to find out more.

  https://www.kdnuggets.com/2020/11/friendly-introduction-graph-neural-networks.html

• Compute Goes Brrr: Revisiting Sutton’s Bitter Lesson for AI

  "It's just about having more compute." Wait, is that really all there is to AI? As Richard Sutton's 'bitter lesson' sinks in for more AI researchers, a debate has stirred that considers a potentially more subtle relationship between advancements in AI based on ever-more-clever algorithms and massively scaled computational power.

  https://www.kdnuggets.com/2020/11/revisiting-sutton-bitter-lesson-ai.html

• How to Acquire the Most Wanted Data Science Skills">How to Acquire the Most Wanted Data Science Skills

  We recently surveyed KDnuggets readers to determine the "most wanted" data science skills. Since they seem to be those most in demand from practitioners, here is a collection of resources for getting started with this learning.

  https://www.kdnuggets.com/2020/11/acquire-most-wanted-data-science-skills.html

• An Introduction to AI, updated">An Introduction to AI, updated

  We provide an introduction to key concepts and methods in AI, covering Machine Learning and Deep Learning, with an updated extensive list that includes Narrow AI, Super Intelligence, and Classic Artificial Intelligence, as well as recent ideas of NeuroSymbolic AI, Neuroevolution, and Federated Learning.

  https://www.kdnuggets.com/2020/10/introduction-ai-updated.html

• PerceptiLabs – A GUI and Visual API for TensorFlow">PerceptiLabs – A GUI and Visual API for TensorFlow

  Recently released PerceptiLabs 0.11, is quickly becoming the GUI and visual API for TensorFlow. PerceptiLabs is built around a sophisticated visual ML modeling editor in which you drag and drop components and connect them together to form your model, automatically creating the underlying TensorFlow code. Try it now.

  https://www.kdnuggets.com/2020/10/perceptilabs-gui-visual-api-tensorflow.html

• Software 2.0 takes shape

  Software developers remain in very high demand as many organizations continue to experience workloads that far exceed available talent. AI-enhanced approaches that automate more areas of the software development lifecycle are in development with interesting potentials for how machine learning and natural language processing can significantly impact how software is designed, developed, tested, and deployed in the future.

  https://www.kdnuggets.com/2020/10/software-20-takes-shape.html

• Can Neural Networks Show Imagination? DeepMind Thinks They Can

  DeepMind has done some of the relevant work in the area of simulating imagination in deep learning systems.

  https://www.kdnuggets.com/2020/09/deepmind-neural-networks-show-imagination.html

• Here’s what you need to look for in a model server to build ML-powered services

  More applications are being infused with machine learning while MLOps processes and best practices are becoming well established. Critical to these software and systems are the servers that run the models, which should feature key capabilities to drive successful enterprise-scale productionizing of machine learning.

  https://www.kdnuggets.com/2020/09/model-server-build-ml-powered-services.html

• AI Papers to Read in 2020

  Reading suggestions to keep you up-to-date with the latest and classic breakthroughs in AI and Data Science.

  https://www.kdnuggets.com/2020/09/ai-papers-read-2020.html

• Modern Data Science Skills: 8 Categories, Core Skills, and Hot Skills">Modern Data Science Skills: 8 Categories, Core Skills, and Hot Skills

  We analyze the results of the Data Science Skills poll, including 8 categories of skills, 13 core skills that over 50% of respondents have, the emerging/hot skills that data scientists want to learn, and what is the top skill that Data Scientists want to learn.

  https://www.kdnuggets.com/2020/09/modern-data-science-skills.html

• Showcasing the Benefits of Software Optimizations for AI Workloads on Intel® Xeon® Scalable Platforms

  The focus of this blog is to bring to light that continued software optimizations can boost performance not only for the latest platforms, but also for the current install base from prior generations. This means customers can continue to extract value from their current platform investments.

  https://www.kdnuggets.com/2020/09/showcasing-benefits-software-optimizations-ai-workloads-intel.html

• Autotuning for Multi-Objective Optimization on LinkedIn’s Feed Ranking

  In this post, the authors share their experience coming up with an automated system to tune one of the main parameters in their machine learning model that recommends content on LinkedIn’s Feed, which is just one piece of the community-focused architecture.

  https://www.kdnuggets.com/2020/08/autotuning-multi-objective-optimization-linkedin-feed-ranking.html

• Going Beyond Superficial: Data Science MOOCs with Substance">Going Beyond Superficial: Data Science MOOCs with Substance

  Data science MOOCs are superficial. At least, a lot of them are. What are your options when looking for something more substantive?

  https://www.kdnuggets.com/2020/08/beyond-superficial-data-science-moocs-substance.html

• KDnuggets™ News 20:n31, Aug 12: Data Science Skills: Have vs Want: Vote in the New Poll; Netflix Polynote is a New Open Source Framework to Build Better Data Science Notebooks

  Vote in the new KDnuggets poll: which data science skills you have and which ones you want? Netflix is not only for movies - its Polynote is a new open source framework to build better data science notebooks; Learn about containerization of PySpark using Kubernetes; Read the findings from Data Scientist Job Market 2020 analysis; and Explore GPT-3 latest.

  https://www.kdnuggets.com/2020/n31.html

• Exploring GPT-3: A New Breakthrough in Language Generation

  GPT-3 is the largest natural language processing (NLP) transformer released to date, eclipsing the previous record, Microsoft Research’s Turing-NLG at 17B parameters, by about 10 times. This has resulted in an explosion of demos: some good, some bad, all interesting.

  https://www.kdnuggets.com/2020/08/exploring-gpt-3-breakthrough-language-generation.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

• Chatbots in a Nutshell

  Marketing scientist Kevin Gray asks Dr. Anna Farzindar of the University of Southern California about chatbots and the ways they are used.

  https://www.kdnuggets.com/2020/05/chatbots-nutshell.html

• Evaluating Ray: Distributed Python for Massive Scalability

  If your team has started using ​Ray​ and you’re wondering what it is, this post is for you. If you’re wondering if Ray should be part of your technical strategy for Python-based applications, especially ML and AI, this post is for you.

  https://www.kdnuggets.com/2020/03/domino-ray-distributed-python-massive-scalability.html

• 50 Must-Read Free Books For Every Data Scientist in 2020">50 Must-Read Free Books For Every Data Scientist in 2020

  In this article, we are listing down some excellent data science books which cover the wide variety of topics under Data Science.

  https://www.kdnuggets.com/2020/03/50-must-read-free-books-every-data-scientist-2020.html

• Python and R Courses for Data Science">Python and R Courses for Data Science

  Since Python and R are a must for today's data scientists, continuous learning is paramount. Online courses are arguably the best and most flexible way to upskill throughout ones career.

  https://www.kdnuggets.com/2020/02/python-r-courses-data-science.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

• The Forgotten Algorithm

  This article explores Monte Carlo Simulation with Streamlit.

  https://www.kdnuggets.com/2020/02/forgotten-algorithm-monte-carlo-simulation.html

• Scaling the Wall Between Data Scientist and Data Engineer

  The educational and research focuses of machine learning tends to highlight the model building, training, testing, and optimization aspects of the data science process. To bring these models into use requires a suite of engineering feats and organization, a standard for which does not yet exist. Learn more about a framework for operating a collaborative data science and engineering team to deploy machine learning models to end-users.

  https://www.kdnuggets.com/2020/02/scaling-wall-data-scientist-data-engineer.html

• Illustrating the Reformer

  In this post, we will try to dive into the Reformer model and try to understand it with some visual guides.

  https://www.kdnuggets.com/2020/02/illustrating-reformer.html

• OpenAI is Adopting PyTorch… They Aren’t Alone

  OpenAI is moving to PyTorch for the bulk of their research work. This might be a high-profile adoption, but it is far from the only such example.

  https://www.kdnuggets.com/2020/01/openai-pytorch-adoption.html

• 2 Questions for a Junior Data Scientist

  Academic credentials and experience with previous machine learning projects are important for kicking off a data science career. However, landing your first job out of school will require you to extend your thinking about projects and problems. Learn how one interviewer honed in on desired skills by considering these two questions.

  https://www.kdnuggets.com/2020/01/questions-junior-data-scientist.html

• NLP Year in Review — 2019

  In this blog post, I want to highlight some of the most important stories related to machine learning and NLP that I came across in 2019.

  https://www.kdnuggets.com/2020/01/nlp-year-review-2019.html

• I wanna be a data scientist, but… how?">I wanna be a data scientist, but… how?

  It’s easy to say "I wanna be a data scientist," but... where do you start? How much time is needed to be desired by companies? Do you need a Master’s degree? Do you need to know every mathematical concept ever derived? The journey might be long, but follow this plan to help you keep moving forward toward your career goal.

  https://www.kdnuggets.com/2020/01/wanna-be-data-scientist.html

• Microsoft Introduces Project Petridish to Find the Best Neural Network for Your Problem">Microsoft Introduces Project Petridish to Find the Best Neural Network for Your Problem

  The new algorithm takes a novel approach to neural architecture search.

  https://www.kdnuggets.com/2020/01/microsoft-introduces-project-petridish-best-neural-network.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

• Google Open Sources MobileNetV3 with New Ideas to Improve Mobile Computer Vision Models

  The latest release of MobileNets incorporates AutoML and other novel ideas in mobile deep learning.

  https://www.kdnuggets.com/2019/12/google-open-sources-mobilenetv3-improve-mobile-computer-vision-models.html

• Can Neural Networks Develop Attention? Google Thinks they Can

  Google recently published some work about modeling attention mechanisms in deep neural networks.

  https://www.kdnuggets.com/2019/11/neural-networks-develop-attention-google.html

• 10 Free Must-read Books on AI">10 Free Must-read Books on AI

  Artificial Intelligence continues to fill the media headlines while scientists and engineers rapidly expand its capabilities and applications. With such explosive growth in the field, there is a great deal to learn. Dive into these 10 free books that are must-reads to support your AI study and work.

  https://www.kdnuggets.com/2019/11/10-free-must-read-books-ai.html

• How to Become a (Good) Data Scientist – Beginner Guide">How to Become a (Good) Data Scientist – Beginner Guide

  A guide covering the things you should learn to become a data scientist, including the basics of business intelligence, statistics, programming, and machine learning.

  https://www.kdnuggets.com/2019/10/good-data-scientist-beginner-guide.html

• Using Neural Networks to Design Neural Networks: The Definitive Guide to Understand Neural Architecture Search

  A recent survey outlined the main neural architecture search methods used to automate the design of deep learning systems.

  https://www.kdnuggets.com/2019/10/using-neural-networks-design-neural-networks-definitive-guide-understand-neural-architecture-search.html

• Introduction to Artificial Neural Networks

  In this article, we’ll try to cover everything related to Artificial Neural Networks or ANN.

  https://www.kdnuggets.com/2019/10/introduction-artificial-neural-networks.html

• OpenAI Tried to Train AI Agents to Play Hide-And-Seek but Instead They Were Shocked by What They Learned

  OpenAI trained agents in a simple game of hide-and-seek and learned many other different skills in the process.

  https://www.kdnuggets.com/2019/10/openai-tried-train-ai-agents-play-hide-seek-instead-shocked-learned.html

• Recreating Imagination: DeepMind Builds Neural Networks that Spontaneously Replay Past Experiences

  DeepMind researchers created a model to be able to replay past experiences in a way that simulate the mechanisms in the hippocampus.

  https://www.kdnuggets.com/2019/10/recreating-imagination-deepmind-builds-neural-networks-spontaneously-replay-past-experiences.html

• How AI will transform healthcare (and can it fix the US healthcare system?)">How AI will transform healthcare (and can it fix the US healthcare system?)

  This thorough review focuses on the impact of AI, 5G, and edge computing on the healthcare sector in the 2020s as well as a look at quantum computing's potential impact on AI, healthcare, and financial services.

  https://www.kdnuggets.com/2019/09/ai-transform-healthcare.html

• My journey path from a Software Engineer to BI Specialist to a Data Scientist">My journey path from a Software Engineer to BI Specialist to a Data Scientist

  The career path of the Data Scientist remains a hot target for many with its continuing high demand. Becoming one requires developing a broad set of skills including statistics, programming, and even business acumen. Learn more about one person's experience making this journey, and discover the many resources available to help you find your way into a world of data science.

  https://www.kdnuggets.com/2019/09/journey-software-engineer-bi-data-scientist.html

• Beyond Neurons: Five Cognitive Functions of the Human Brain that we are Trying to Recreate with Artificial Intelligence

  The quest for recreating cognitive capabilities of the brain in deep neural networks remains one of the elusive goals of AI. Let’s explore some human cognitive skills that are serving as inspiration to a new generation of AI techniques.

  https://www.kdnuggets.com/2019/09/beyond-neurons-five-cognitive-functions-human-brain-recreate-artificial-intelligence.html

• TensorFlow 2.0: Dynamic, Readable, and Highly Extended

  With substantial changes coming with TensorFlow 2.0, and the release candidate version now available, learn more in this guide about the major updates and how to get started on the machine learning platform.

  https://www.kdnuggets.com/2019/08/tensorflow-20.html

• Is Kaggle Learn a “Faster Data Science Education?”">Is Kaggle Learn a “Faster Data Science Education?”

  Kaggle Learn is "Faster Data Science Education," featuring micro-courses covering an array of data skills for immediate application. Courses may be made with newcomers in mind, but the platform and its content is proving useful as a review for more seasoned practitioners as well.

  https://www.kdnuggets.com/2019/08/kaggle-learn-faster-data-science-education.html

• How to Become More Marketable as a Data Scientist">How to Become More Marketable as a Data Scientist

  As a data scientist, you are in high demand. So, how can you increase your marketability even more? Check out these current trends in skills most desired by employers in 2019.

  https://www.kdnuggets.com/2019/08/marketable-data-scientist.html

• Inside Pluribus: Facebook’s New AI That Just Mastered the World’s Most Difficult Poker Game

  The reasons why Pluribus represents a major breakthrough in AI systems might result confusing to many readers. After all, in recent years AI researchers have made tremendous progress across different complex games. However, six-player, no-limit Texas Hold’em still remains one of the most elusive challenges for AI systems.

  https://www.kdnuggets.com/2019/08/inside-pluribus-facebooks-new-ai-poker.html

• 7 Tips for Dealing With Small Data

  At my workplace, we produce a lot of functional prototypes for our clients. Because of this, I often need to make Small Data go a long way. In this article, I’ll share 7 tips to improve your results when prototyping with small datasets.

  https://www.kdnuggets.com/2019/07/7-tips-dealing-small-data.html

• Top 13 Skills To Become a Rockstar Data Scientist">Top 13 Skills To Become a Rockstar Data Scientist

  Education, coding, SQL, big data platforms, storytelling and more. These are the 13 skills you need to master to become a rockstar data scientist.

  https://www.kdnuggets.com/2019/07/top-13-skills-become-rockstar-data-scientist.html

• State of AI Report 2019">State of AI Report 2019

  This year's "State of AI Report" has been released. Read it to find out about the latest in AI research, talent, industry, and politics form the past 12 months.

  https://www.kdnuggets.com/2019/07/state-ai-report-2019.html

• Spark NLP: Getting Started With The World’s Most Widely Used NLP Library In The Enterprise"> Spark NLP: Getting Started With The World’s Most Widely Used NLP Library In The Enterprise

  The Spark NLP library has become a popular AI framework that delivers speed and scalability to your projects. Check out what's under the hood and learn about how to getting started leveraging Spark NLP from John Snow Labs.

  https://www.kdnuggets.com/2019/06/spark-nlp-getting-started-with-worlds-most-widely-used-nlp-library-enterprise.html

• Evolving Deep Neural Networks

  This article reviews how evolutionary algorithms have been proposed and tested as a competitive alternative to address a number of issues related to neural network design.

  https://www.kdnuggets.com/2019/06/evolving-deep-neural-networks.html

• Data Science vs. Decision Science

  Data science and decision science are related but still separate fields, so at some points, it might be hard to compare them directly. We attempted to show our vision of the commonalities, differences, and specific features of data science and decision science.

  https://www.kdnuggets.com/2019/05/data-science-vs-decision-science.html

• Was it Worth Studying a Data Science Masters?

  As I started to apply for Data Science roles it quickly became apparent that I was lacking two key skills: applying Machine Learning and coding

  https://www.kdnuggets.com/2019/04/worth-studying-data-science-masters.html

• Distributed Artificial Intelligence: A primer on Multi-Agent Systems, Agent-Based Modeling, and Swarm Intelligence

  Distributed Artificial Intelligence (DAI) is a class of technologies and methods that span from swarm intelligence to multi-agent technologies. It is one of the subsets of AI where simulation has greater importance that point-prediction.

  https://www.kdnuggets.com/2019/04/distributed-artificial-intelligence-multi-agent-systems-agent-based-modeling-swarm-intelligence.html

• An introduction to explainable AI, and why we need it

  We introduce explainable AI, why it is needed, and present the Reversed Time Attention Model, Local Interpretable Model-Agnostic Explanation and Layer-wise Relevance Propagation.

  https://www.kdnuggets.com/2019/04/introduction-explainable-ai.html

• Explainable AI or Halting Faulty Models ahead of Disaster

  A brief overview of a new method for explainable AI (XAI), called anchors, introduce its open-source implementation and show how to use it to explain models predicting the survival of Titanic passengers.

  https://www.kdnuggets.com/2019/03/explainable-ai.html

• 3 Reasons Why AutoML Won’t Replace Data Scientists Yet

  We dispel the myth that AutoML is replacing Data Scientists jobs by highlighting three factors in Data Science development that AutoML can’t solve.

  https://www.kdnuggets.com/2019/03/why-automl-wont-replace-data-scientists.html

• The Difference Between Data Scientists and Data Engineers

  ODSC East 2019 has multiple tracks for both Data Scientists and Data Engineers, including workshops, talks, and training sessions. Save 45% with code KDN45.

  https://www.kdnuggets.com/2019/03/odsc-difference-data-scientists-data-engineers.html

• On Building Effective Data Science Teams

  We take a look at the qualities that make a successful data team in order to help business leaders and executives create better AI strategies.

  https://www.kdnuggets.com/2019/03/building-effective-data-science-teams.html

• OpenAI’s GPT-2: the model, the hype, and the controversy

  OpenAI recently released a very large language model called GPT-2. Controversially, they decided not to release the data or the parameters of their biggest model, citing concerns about potential abuse. Read this researcher's take on the issue.

  https://www.kdnuggets.com/2019/03/openai-gpt-2-model-hype-controversy.html

• Are BERT Features InterBERTible?

  This is a short analysis of the interpretability of BERT contextual word representations. Does BERT learn a semantic vector representation like Word2Vec?

  https://www.kdnuggets.com/2019/02/bert-features-interbertible.html

• A comprehensive survey on graph neural networks

  This article summarizes a paper which presents us with a broad sweep of the graph neural network landscape. It’s a survey paper, so you’ll find details on the key approaches and representative papers, as well as information on commonly used datasets and benchmark performance on them.

  https://www.kdnuggets.com/2019/02/comprehensive-survey-graph-neural-networks.html

• 10 Exciting Ideas of 2018 in NLP

  We outline a selection of exciting developments in NLP from the last year, and include useful recent papers and images to help further assist with your learning.

  https://www.kdnuggets.com/2019/01/10-exciting-ideas-2018-nlp.html

• Should you become a data scientist?">Should you become a data scientist?

  An overview of the current situation for data scientists, from its origins and history, to the recent growth in job postings, and looking at what changes the future might bring.

  https://www.kdnuggets.com/2018/12/should-i-become-a-data-scientist.html

• AI, Data Science, Analytics Main Developments in 2018 and Key Trends for 2019">AI, Data Science, Analytics Main Developments in 2018 and Key Trends for 2019

  Review of 2018 and Predictions for 2019 from our panel of experts, including Meta Brown, Tom Davenport, Carla Gentry, Bob E Hayes, Cassie Kozyrkov, Doug Laney, Bill Schmarzo, Kate Strachnyi, Ronald van Loon, Favio Vazquez, and Jen Underwood.

  https://www.kdnuggets.com/2018/12/predictions-data-science-analytics-2019.html

• Top KDnuggets tweets, Nov 21-27: Intro to #DataScience for Managers – a mindmap; An Introduction to #AI

  Also: An Introduction to #AI; Intuitively Understanding Convolutions for #DeepLearning; 10 Free Must-See Courses for Machine Learning and Data Science.

  https://www.kdnuggets.com/2018/11/top-tweets-nov21-27.html

• Intro to Data Science for Managers">Intro to Data Science for Managers

  This mindmap contains a condensed introduction to the key data science concepts and techniques that have revolutionized the business landscape and became essential for making beneficial data-driven decisions

  https://www.kdnuggets.com/2018/11/intro-data-science-managers.html

• An Introduction to AI">An Introduction to AI

  We provide an introduction to AI key terminologies and methodologies, covering both Machine Learning and Deep Learning, with an extensive list including Narrow AI, Super Intelligence, Classic Artificial Intelligence, and more.

  https://www.kdnuggets.com/2018/11/an-introduction-ai.html

• Anticipating the next move in data science – my interview with Thomson Reuters

  Like chess, Big Data is a combination of science, art and play; Gregory Piatetsky-Shapiro of KDnuggets helps data devotees discover winning moves - my Thomson Reuters interview.

  https://www.kdnuggets.com/2018/11/gps-anticipating-next-move-data-science.html

• Semantic Segmentation: Wiki, Applications and Resources

  An extensive overview covering the features of Semantic Segmentation and possible uses for it, including GeoSensing, Autonomous Drive, Facial Recognition and more.

  https://www.kdnuggets.com/2018/10/semantic-segmentation-wiki-applications-resources.html

• Data Science Predicting The Future

  In this article we will expand on the knowledge learnt from the last article - The What, Where and How of Data for Data Science - and consider how data science is applied to predict the future.

  https://www.kdnuggets.com/2018/06/data-science-predicting-future.html

• 9 Must-have skills you need to become a Data Scientist, updated">9 Must-have skills you need to become a Data Scientist, updated

  Check out this collection of 9 (plus some additional freebies) must-have skills for becoming a data scientist.

  https://www.kdnuggets.com/2018/05/simplilearn-9-must-have-skills-data-scientist.html

• Top 10 Technology Trends of 2018">Top 10 Technology Trends of 2018

  In this article, we will focus on the modern trends that took off well on the market by the end of 2017 and discuss the major breakthroughs expected in 2018.

  https://www.kdnuggets.com/2018/04/top-10-technology-trends-2018.html

• The Current Hype Cycle in Artificial Intelligence

  Over the past decade, the field of artificial intelligence (AI) has seen striking developments. As surveyed in, there now exist over twenty domains in which AI programs are performing at least as well as (if not better than) humans.

  https://www.kdnuggets.com/2018/02/current-hype-cycle-artificial-intelligence.html

• Where AI is already rivaling humans

  Since 2011, AI hit hypergrowth, and researchers have created several AI solutions that are almost as good as – or better than – humans in several domains, including games, healthcare, computer vision and object recognition, speech to text conversion, speaker recognition, and improved robots and chat-bots for solving specific problems.

  https://www.kdnuggets.com/2018/02/domains-ai-rivaling-humans.html

• 5 Things You Need To Know About Data Science

  Here are 5 useful things to know about Data Science, including its relationship to BI, Data Mining, Predictive Analytics, and Machine Learning; Data Scientist job prospects; where to learn Data Science; and which algorithms/methods are used by Data Scientists

  https://www.kdnuggets.com/2018/02/5-things-about-data-science.html

• Using Genetic Algorithm for Optimizing Recurrent Neural Networks

  In this tutorial, we will see how to apply a Genetic Algorithm (GA) for finding an optimal window size and a number of units in Long Short-Term Memory (LSTM) based Recurrent Neural Network (RNN).

  https://www.kdnuggets.com/2018/01/genetic-algorithm-optimizing-recurrent-neural-network.html

• Custom Optimizer in TensorFlow

  How to customize the optimizers to speed-up and improve the process of finding a (local) minimum of the loss function using TensorFlow.

  https://www.kdnuggets.com/2018/01/custom-optimizer-tensorflow.html

• Artificial General Intelligence (AGI) in less than 50 years, say KDnuggets readers

  Artificial General Intelligence (AGI) will likely be achieved in less than 50 years, according to latest KDnuggets Poll. The median estimate from all regions was 21-50 years, except in Asia where AGI is expected in 11-20 years.

  https://www.kdnuggets.com/2018/01/poll-agi-50-years.html

• Big Data: Main Developments in 2017 and Key Trends in 2018">Big Data: Main Developments in 2017 and Key Trends in 2018

  As we bid farewell to one year and look to ring in another, KDnuggets has solicited opinions from numerous Big Data experts as to the most important developments of 2017 and their 2018 key trend predictions.

  https://www.kdnuggets.com/2017/12/big-data-main-developments-2017-key-trends-2018.html

• What is a Bayesian Neural Network?">What is a Bayesian Neural Network?

  BNNs are important in specific settings, especially when we care about uncertainty very much.

  https://www.kdnuggets.com/2017/12/what-bayesian-neural-network.html

• AlphaGo Zero: The Most Significant Research Advance in AI">AlphaGo Zero: The Most Significant Research Advance in AI

  The previous version of AlphaGo beat the human world champion in 2016. The new AlphaGo Zero beat the previous version by 100 games to 0, and learned Go completely on its own. We examine what this means for AI.

  https://www.kdnuggets.com/2017/10/alphago-zero-biggest-ai-advance.html

• Top Quora Data Science Writers and Their Best Advice, Updated

  Get some insight into tips and tricks, the future of the field, career advice, code snippets, and more from the top data science writers on Quora.

  https://www.kdnuggets.com/2017/07/top-quora-data-science-writers-best-advice-updated.html

• The dynamics between AI and IoT

  We see the need for a new type of Engineer who will combine knowledge from Electronics & IoT with Machine learning, AI, Robotics, Cloud and Data management (devops).

  https://www.kdnuggets.com/2017/04/dynamics-ai-iot.html

• A Brief History of Artificial Intelligence">A Brief History of Artificial Intelligence

  This post is a brief outline of what happened in artificial intelligence in the last 60 years. A great place to start or brush up on your history.
   
   

  https://www.kdnuggets.com/2017/04/brief-history-artificial-intelligence.html

• What I Learned Implementing a Classifier from Scratch in Python

  In this post, the author implements a machine learning algorithm from scratch, without the use of a library such as scikit-learn, and instead writes all of the code in order to have a working binary classifier algorithm.

  https://www.kdnuggets.com/2017/02/learned-implementing-classifier-scratch-python.html

• 5 Free Courses for Getting Started in Artificial Intelligence

  A carefully-curated list of 5 free collections of university course material to help you better understand the various aspects of what artificial intelligence and skills necessary for moving forward in the field.

  https://www.kdnuggets.com/2017/02/5-free-courses-getting-started-artificial-intelligence.html

• Artificial Intelligence and Speech Recognition for Chatbots: A Primer

  Bot bots bots... Read this overview of how artificial intelligence and natural language processing are contributing to chatbot development, and where it all goes from here.

  https://www.kdnuggets.com/2017/01/artificial-intelligence-speech-recognition-chatbots-primer.html

• ResNets, HighwayNets, and DenseNets, Oh My!

  This post walks through the logic behind three recent deep learning architectures: ResNet, HighwayNet, and DenseNet. Each make it more possible to successfully trainable deep networks by overcoming the limitations of traditional network design.

  https://www.kdnuggets.com/2016/12/resnets-highwaynets-densenets-oh-my.html

• Artificial Intelligence and Life in 2030

  Read this engaging overview of a report from the Stanford University 100 year study of Artificial Intelligence, “a long-term investigation of the field of Artificial Intelligence (AI) and its influences on people, their communities, and society.”

  https://www.kdnuggets.com/2016/12/artificial-intelligence-life-2030.html

• Data Science, Predictive Analytics Main Developments in 2016 and Key Trends for 2017">Data Science, Predictive Analytics Main Developments in 2016 and Key Trends for 2017

  Key themes included the polling failures in 2016 US Elections, Deep Learning, IoT, greater focus on value and ROI, and increasing adoption of predictive analytics by the "masses" of industry.
   
  

  https://www.kdnuggets.com/2016/12/data-science-predictive-analytics-main-developments-trends.html

• Data Analytics Models in Quantitative Finance and Risk Management

  We review how key data science algorithms, such as regression, feature selection, and Monte Carlo, are used in financial instrument pricing and risk management.

  https://www.kdnuggets.com/2016/12/data-analytics-models-quantitative-finance-risk-management.html

• Data Science for Internet of Things (IoT): Ten Differences From Traditional Data Science">Data Science for Internet of Things (IoT): Ten Differences From Traditional Data Science

  The connected devices (The Internet of Things) generate more than 2.5 quintillion bytes of data daily. All this data will significantly impact business processes and the Data Science for IoT will take increasingly central role. Here we outline 10 main differences between Data Science for IoT and traditional Data Science.

  https://www.kdnuggets.com/2016/09/data-science-iot-10-differences.html

• The Evolution of IoT Edge Analytics: Strategies of Leading Players

  This article explores the significance and evolution of IoT edge analytics. Since the author believes that hardware capabilities will converge for large vendors, IoT analytics will be the key differentiator.

  https://www.kdnuggets.com/2016/09/evolution-iot-edge-analytics.html