Search results for Foundation Models

Found 568 documents, 5970 searched:

• Paradoxes in Data Science

  Have a look into some of the main paradoxes associate with Data Science and it’s statistical foundations.

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

• What Is The Real Difference Between Data Engineers and Data Scientists?

  To launch your data career, you’ll need both theoretical knowledge and applied skills. Bootcamp programs like Springboard’s Data Science Career Track and Data Engineering Career Track can help make you job-ready through hands-on, project-based learning and one-on-one mentorship. Wondering which data career path is right for you? Read on to find out.

  https://www.kdnuggets.com/2021/09/springboard-difference-data-engineers-data-scientists.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

• ebook: Learn Data Science with R – free download

  Check out this new book for data science beginners with many practical examples that covers statistics, R, graphing, and machine learning. As a source to learn the full breadth of data science foundations, "Learn Data Science with R" starts at the beginner level and gradually progresses into expert content.

  https://www.kdnuggets.com/2021/09/ebook-learn-data-science-r.html

• Five Key Facts About Wu Dao 2.0: The Largest Transformer Model Ever Built

  The record-setting model combines some clever research and engineering methods.

  https://www.kdnuggets.com/2021/09/five-key-facts-wu-dao-largest-transformer-model.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

• Enhancing Machine Learning Personalization through Variety

  Personalization drives growth and is a touchstone of good customer experience. Personalization driven through machine learning can enable companies to improve this experience while improving ROI for marketing campaigns. However, challenges exist in these techniques for when personalization makes sense and how and when specific options are recommended.

  https://www.kdnuggets.com/2021/08/machine-learning-personalization-variety.html

• 15 Things I Look for in Data Science Candidates

  This article presents advice for anyone looking or hiring for data science jobs, written by someone with practical and useful insight.

  https://www.kdnuggets.com/2021/08/15-things-data-science-candidates.html

• Agile Data Labeling: What it is and why you need it

  The notion of Agile in software development has made waves across industries with its revolution for productivity. Can the same benefits be applied to the often arduous task of annotating data sets for machine learning?

  https://www.kdnuggets.com/2021/08/agile-data-labeling.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

• MLOps And Machine Learning Roadmap

  A 16–20 week roadmap to review machine learning and learn MLOps.

  https://www.kdnuggets.com/2021/08/mlops-machine-learning-roadmap.html

• The Difference Between Data Scientists and ML Engineers">The Difference Between Data Scientists and ML Engineers

  What's the difference? Responsibilities, expertise, and salary expectations.

  https://www.kdnuggets.com/2021/08/difference-between-data-scientists-ml-engineers.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

• Advice for Learning Data Science from Google’s Director of Research">Advice for Learning Data Science from Google’s Director of Research

  Surfing the professional career wave in data science is a hot prospect for many looking to get their start in the world. The digital revolution continues to create many exciting new opportunities. But, jumping in too fast without fully establishing your foundational skills can be detrimental to your success, as is suggested by this advice for data science newbies from Peter Norvig, the Director of Research at Google.

  https://www.kdnuggets.com/2021/07/google-advice-learning-data-science.html

• Top 6 Data Science Online Courses in 2021">Top 6 Data Science Online Courses in 2021

  As an aspiring data scientist, it is easy to get overwhelmed by the abundance of resources available on the Internet. With these 6 online courses, you can develop yourself from a novice to experienced in less than a year, and prepare you with the skills necessary to land a job in data science.

  https://www.kdnuggets.com/2021/07/top-6-data-science-online-courses.html

• Data Scientists and ML Engineers Are Luxury Employees">Data Scientists and ML Engineers Are Luxury Employees

  Maybe it seems that everyone wants to become a data scientist and every organization wants to hire one as quickly as possible. However, a mismatch often exists between what companies tend to need and what ML practitioners want to do. So, it's time for the field to take another step toward maturity through an enhanced appreciation of the broad range of technical foundations for an organization to become data-driven.

  https://www.kdnuggets.com/2021/07/data-scientists-machine-learning-engineers-luxury-employees.html

• Computational Complexity of Deep Learning: Solution Approaches

  Why has deep learning been so successful? What is the fundamental reason that deep learning can learn from big data? Why cannot traditional ML learn from the large data sets that are now available for different tasks as efficiently as deep learning can?

  https://www.kdnuggets.com/2021/06/computational-complexity-deep-learning-solution-approaches.html

• Unleashing the Power of MLOps and DataOps in Data Science

  Organizations trying to move forward with analytics and data science initiatives -- while floating in an ocean of data -- must enhance their overall approach and culture to embrace a foundation on DataOps and MLOps. Leveraging these operational frameworks are necessary to enable the data to generate real business value.

  https://www.kdnuggets.com/2021/06/power-mlops-dataops-data-science.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

• An introduction to Explainable AI (XAI) and Explainable Boosting Machines (EBM)

  Understanding why your AI-based models make the decisions they do is crucial for deploying practical solutions in the real-world. Here, we review some techniques in the field of Explainable AI (XAI), why explainability is important, example models of explainable AI using LIME and SHAP, and demonstrate how Explainable Boosting Machines (EBMs) can make explainability even easier.

  https://www.kdnuggets.com/2021/06/explainable-ai-xai-explainable-boosting-machines-ebm.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

• Choosing the Right BI Tool for Your Business

  Here are six questions to ask as you search for the best BI tool for your specific needs.

  https://www.kdnuggets.com/2021/05/choosing-right-bi-tool-business.html

• Awesome list of datasets in 100+ categories

  With an estimated 44 zettabytes of data in existence in our digital world today and approximately 2.5 quintillion bytes of new data generated daily, there is a lot of data out there you could tap into for your data science projects. It's pretty hard to curate through such a massive universe of data, but this collection is a great start. Here, you can find data from cancer genomes to UFO reports, as well as years of air quality data to 200,000 jokes. Dive into this ocean of data to explore as you learn how to apply data science techniques or leverage your expertise to discover something new.

  https://www.kdnuggets.com/2021/05/awesome-list-datasets.html

• Best Python Books for Beginners and Advanced Programmers

  Let's take a look at nine of the best Python books for both beginners and advanced programmers, covering topics such as data science, machine learning, deep learning, NLP, and more.

  https://www.kdnuggets.com/2021/05/best-python-books-beginner-advanced.html

• Essential Linear Algebra for Data Science and Machine Learning">Essential Linear Algebra for Data Science and Machine Learning

  Linear algebra is foundational in data science and machine learning. Beginners starting out along their learning journey in data science--as well as established practitioners--must develop a strong familiarity with the essential concepts in linear algebra.

  https://www.kdnuggets.com/2021/05/essential-linear-algebra-data-science-machine-learning.html

• Feature stores – how to avoid feeling that every day is Groundhog Day

  Feature stores stop the duplication of each task in the ML lifecycle. You can reuse features and pipelines for different models, monitor models consistently, and sidestep data leakage with this MLOps technology that everyone is talking about.

  https://www.kdnuggets.com/2021/05/feature-stores-how-avoid-feeling-every-day-is-groundhog-day.html

• What is Adversarial Neural Cryptography?

  The novel approach combines GANs and cryptography in a single, powerful security method.

  https://www.kdnuggets.com/2021/04/adversarial-neural-cryptography.html

• 3 More Free Top Notch Natural Language Processing Courses

  Are you looking to continue your learning of natural language processing? This small collection of 3 free top notch courses will allow you to do just that.

  https://www.kdnuggets.com/2021/03/3-more-free-nlp-courses.html

• Top 10 Python Libraries Data Scientists should know in 2021">Top 10 Python Libraries Data Scientists should know in 2021

  So many Python libraries exist that offer powerful and efficient foundations for supporting your data science work and machine learning model development. While the list may seem overwhelming, there are certain libraries you should focus your time on, as they are some of the most commonly used today.

  https://www.kdnuggets.com/2021/03/top-10-python-libraries-2021.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

• 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

• 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

• 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

• Data Science vs Business Intelligence, Explained">Data Science vs Business Intelligence, Explained

  Knowing the differences between the business intelligence and data science is more than just a matter of semantics.

  https://www.kdnuggets.com/2021/02/data-science-vs-business-intelligence-explained.html

• Baidu Research: 10 Technology Trends in 2021

  Understanding future technology trends may never have been as important as it is today. Check out the prediction of the 10 technology trends in 2021 from Baidu Research.

  https://www.kdnuggets.com/2021/01/top-10-technology-trends-2021.html

• The Ultimate Scikit-Learn Machine Learning Cheatsheet">The Ultimate Scikit-Learn Machine Learning Cheatsheet

  With the power and popularity of the scikit-learn for machine learning in Python, this library is a foundation to any practitioner's toolset. Preview its core methods with this review of predictive modelling, clustering, dimensionality reduction, feature importance, and data transformation.

  https://www.kdnuggets.com/2021/01/ultimate-scikit-learn-machine-learning-cheatsheet.html

• Graph Representation Learning: The Free eBook

  This free eBook can show you what you need to know to leverage graph representation in data science, machine learning, and neural network models.

  https://www.kdnuggets.com/2021/01/graph-representation-learning-book-free-ebook.html

• Build a Data Science Portfolio that Stands Out Using These Platforms">Build a Data Science Portfolio that Stands Out Using These Platforms

  Making your big break into the data science profession means standing out to potential employers in a crowd of tough competition. An important way to showcase your skills and experience is through the presentation of a portfolio. Following these recommendations for developing your portfolio will help you network effectively and stay on top of an ever-changing field.

  https://www.kdnuggets.com/2021/01/build-data-science-portfolio.html

• 5 Tools for Effortless Data Science

  The sixth tool is coffee.

  https://www.kdnuggets.com/2021/01/5-tools-effortless-data-science.html

• Attention mechanism in Deep Learning, Explained

  Attention is a powerful mechanism developed to enhance the performance of the Encoder-Decoder architecture on neural network-based machine translation tasks. Learn more about how this process works and how to implement the approach into your work.

  https://www.kdnuggets.com/2021/01/attention-mechanism-deep-learning-explained.html

• Meet whale! The stupidly simple data discovery tool">Meet whale! The stupidly simple data discovery tool

  Finding data and understanding its meaning represents the traditional "daily grind" of a Data Scientist. With whale, the new lightweight data discovery, documentation, and quality engine for your data warehouse that is under development by Dataframe, your data science team will more efficiently search data and automate its data metrics.

  https://www.kdnuggets.com/2020/12/whale-data-discovery-tool.html

• 15 Free Data Science, Machine Learning & Statistics eBooks for 2021">15 Free Data Science, Machine Learning & Statistics eBooks for 2021

  We present a curated list of 15 free eBooks compiled in a single location to close out the year.

  https://www.kdnuggets.com/2020/12/15-free-data-science-machine-learning-statistics-ebooks-2021.html

• Data Science as a Product – Why Is It So Hard?

  Developing machine learning models as products that deliver business value remains a new field with uncharted paths toward success. Applying well-established software development approaches, such as agile, is not straightforward, but may still offer a solid foundation to guide success.

  https://www.kdnuggets.com/2020/12/data-science-product-hard.html

• Data Science and Machine Learning: The Free eBook

  Check out the newest addition to our free eBook collection, Data Science and Machine Learning: Mathematical and Statistical Methods, and start building your statistical learning foundation today.

  https://www.kdnuggets.com/2020/12/data-science-machine-learning-free-ebook.html

• Facebook Open Sources ReBeL, a New Reinforcement Learning Agent

  The new model tries to recreate the reinforcement learning and search methods used by AlphaZero in imperfect information scenarios.

  https://www.kdnuggets.com/2020/12/facebook-open-sources-rebel-new-reinforcement-learning-agent.html

• AI registers: finally, a tool to increase transparency in AI/ML

  Transparency, explainability, and trust are pressing topics in AI/ML today. While much has been written about why they are important and what you need to do, no tools have existed until now.

  https://www.kdnuggets.com/2020/12/ai-registers-transparency-ml.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

• The Ultimate Guide to Data Engineer Interviews

  If you are preparing for data engineering interviews, then follow these technical recommendations regarding your resume, programming skills, SQL acumen, and system design problem-solving, as well as the non-technical aspects of your upcoming interview session.

  https://www.kdnuggets.com/2020/12/ultimate-guide-data-engineer-interviews.html

• Introduction to Data Engineering">Introduction to Data Engineering

  The Q&A for the most frequently asked questions about Data Engineering: What does a data engineer do? What is a data pipeline? What is a data warehouse? How is a data engineer different from a data scientist? What skills and programming languages do you need to learn to become a data engineer?

  https://www.kdnuggets.com/2020/12/introduction-data-engineering.html

• Know-How to Learn Machine Learning Algorithms Effectively

  The takeaway from the story is that machine learning is way beyond a simple fit and predict methods. The author shares their approach to actually learning these algorithms beyond the surface.

  https://www.kdnuggets.com/2020/11/learn-machine-learning-algorithms-effectively.html

• How Machine Learning Works for Social Good

  We often discuss applying data science and machine learning techniques in term so of how they help your organization or business goals. But, these algorithms aren't limited to only increasing the bottom line. Developing new applications that leverage the predictive power of AI to benefit society and those communities in need is an equally valuable endeavor for Data Scientists that will further expand the positive impact of machine learning to the world.

  https://www.kdnuggets.com/2020/11/machine-learning-social-good.html

• Top 6 Data Science Programs for Beginners

  Udacity has the best industry-leading programs in data science. Here are the top six data science courses for beginners to help you get started.

  https://www.kdnuggets.com/2020/11/udacity-data-science-programs-beginners.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

• Is Data Science for Me? 14 Self-examination Questions to Consider">Is Data Science for Me? 14 Self-examination Questions to Consider

  You are intrigued by this exciting new field of Data Science, and you think you want in on the action. The demand remains very high and the salaries are strong. Before taking the leap onto this path, these questions will help you evaluate if you are ready for the challenges and opportunities.

  https://www.kdnuggets.com/2020/11/data-science-14-self-examination-questions.html

• My Data Science Online Learning Journey on Coursera

  Check out the author's informative list of courses and specializations on Coursera taken to get started on their data science and machine learning journey.

  https://www.kdnuggets.com/2020/11/data-science-online-learning-journey-coursera.html

• Essential data science skills that no one talks about">Essential data science skills that no one talks about

  Old fashioned engineering skills are what you need to boost your data science career.

  https://www.kdnuggets.com/2020/11/essential-data-science-skills-no-one-talks-about.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

• 5 Must-Read Data Science Papers (and How to Use Them)

  Keeping ahead of the latest developments in a field is key to advancing your skills and your career. Five foundational ideas from recent data science papers are highlighted here with tips on how to leverage these advancements in your work, and keep you on top of the machine learning game.

  https://www.kdnuggets.com/2020/10/5-must-read-data-science-papers.html

• Software Engineering Tips and Best Practices for Data Science">Software Engineering Tips and Best Practices for Data Science

  Bringing your work as a Data Scientist into the real-world means transforming your experiments, test, and detailed analysis into great code that can be deployed as efficient and effective software solutions. You must learn how to enable your machine learning algorithms to integrate with IT systems by taking them out of your notebooks and delivering them to the business by following software engineering standards.

  https://www.kdnuggets.com/2020/10/software-engineering-best-practices-data-science.html

• 10 Best Machine Learning Courses in 2020">10 Best Machine Learning Courses in 2020

  If you are ready to take your career in machine learning to the next level, then these top 10 Machine Learning Courses covering both practical and theoretical work will help you excel.

  https://www.kdnuggets.com/2020/10/10-best-machine-learning-courses-2020.html

• The Online Courses You Must Take to be a Better Data Scientist

  These select courses have proved to be precious online resources which helped make the author a better data scientist today.

  https://www.kdnuggets.com/2020/09/online-courses-better-data-scientist.html

• Causal Inference: The Free eBook

  Here's another free eBook for those looking to up their skills. If you are seeking a resource that exhaustively treats the topic of causal inference, this book has you covered.

  https://www.kdnuggets.com/2020/09/causal-inference-free-ebook.html

• Machine Learning from Scratch: Free Online Textbook">Machine Learning from Scratch: Free Online Textbook

  If you are looking for a machine learning starter that gets right to the core of the concepts and the implementation, then this new free textbook will help you dive in to ML engineering with ease. By focusing on the basics of the underlying algorithms, you will be quickly up and running with code you construct yourself.

  https://www.kdnuggets.com/2020/09/machine-learning-from-scratch-free-online-textbook.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

• Online Certificates/Courses in AI, Data Science, Machine Learning from Top Universities">Online Certificates/Courses in AI, Data Science, Machine Learning from Top Universities

  We present the online courses and certificates in AI, Data Science, Machine Learning, and related topics from the top 20 universities in the world.

  https://www.kdnuggets.com/2020/09/online-certificates-ai-data-science-machine-learning-top.html

• The Maslow’s hierarchy your data science team needs

  Domino Data Lab was announced as a leader for the second year in a row in the recently released “Forrester Wave™: Notebook-based Predictive Analytics and Machine Learning (PAML), Q3 2020” analyst report. True to our data science roots, we’ve built a Maslow’s hierarchy of data science team needs.

  https://www.kdnuggets.com/2020/09/domino-leader-forrester-paml-data-science-team.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

• Deep Learning’s Most Important Ideas">Deep Learning’s Most Important Ideas

  In the field of deep learning, there continues to be a deluge of research and new papers published daily. Many well-adopted ideas that have stood the test of time provide the foundation for much of this new work. To better understand modern deep learning, these techniques cover the basic necessary knowledge, especially as a starting point if you are new to the field.

  https://www.kdnuggets.com/2020/09/deep-learnings-most-important-ideas.html

• Statistics with Julia: The Free eBook">Statistics with Julia: The Free eBook

  This free eBook is a draft copy of the upcoming Statistics with Julia: Fundamentals for Data Science, Machine Learning and Artificial Intelligence. Interested in learning Julia for data science? This might be the best intro out there.

  https://www.kdnuggets.com/2020/09/statistics-julia-free-ebook.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

• Which methods should be used for solving linear regression?

  As a foundational set of algorithms in any machine learning toolbox, linear regression can be solved with a variety of approaches. Here, we discuss. with with code examples, four methods and demonstrate how they should be used.

  https://www.kdnuggets.com/2020/09/solving-linear-regression.html

• Top Online Masters in Analytics, Business Analytics, Data Science – Updated">Top Online Masters in Analytics, Business Analytics, Data Science – Updated

  We provide an updated list of best online Masters in AI, Analytics, and Data Science, including rankings, tuition, and duration of the education program.

  https://www.kdnuggets.com/2020/09/best-online-masters-data-science-analytics-online.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

• 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

• A Tour of End-to-End Machine Learning Platforms

  An end-to-end machine learning platform needs a holistic approach. If you’re interested in learning more about a few well-known ML platforms, you’ve come to the right place!

  https://www.kdnuggets.com/2020/07/tour-end-to-end-machine-learning-platforms.html

• What I learned from looking at 200 machine learning tools

  While hundreds of machine learning tools are available today, the ML software landscape may still be underdeveloped with more room to mature. This review considers the state of ML tools, existing challenges, and which frameworks are addressing the future of machine learning software.

  https://www.kdnuggets.com/2020/07/200-machine-learning-tools.html

• Data Mining and Machine Learning: Fundamental Concepts and Algorithms: The Free eBook

  The second edition of Data Mining and Machine Learning: Fundamental Concepts and Algorithms is available to read freely online, and includes a new part on regression with chapters on linear regression, logistic regression, neural networks, deep learning and regression assessment.

  https://www.kdnuggets.com/2020/07/data-mining-machine-learning-free-ebook.html

• Data Science MOOCs are too Superficial">Data Science MOOCs are too Superficial

  Most massive open online courses are too superficial because they offer introductory-level courses. For in-depth knowledge, more is needed to increase your knowledge and expertise after establishing a foundation.

  https://www.kdnuggets.com/2020/07/data-science-moocs-superficial.html

• Math and Architectures of Deep Learning!

  This hands-on book bridges the gap between theory and practice, showing you the math of deep learning algorithms side by side with an implementation in PyTorch. Save 50% with code kdarch50.

  https://www.kdnuggets.com/2020/07/manning-math-architectures-deep-learning.html

• An Introduction to Statistical Learning: The Free eBook

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

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

• Free Economics & Finance Courses for Data Scientists

  Here is a selection of courses for those interested in diversifying their domain knowledge into the related realms of economics and finance, with the goal of being able to apply your data science skills to these domains.

  https://www.kdnuggets.com/2020/06/free-economics-finance-courses-data-scientists.html

• 4 Free Math Courses to do and Level up your Data Science Skills">4 Free Math Courses to do and Level up your Data Science Skills

  Just as there is no Data Science without data, there's no science in data without mathematics. Strengthening your foundational skills in math will level you up as a data scientist that will enable you to perform with greater expertise.

  https://www.kdnuggets.com/2020/06/4-free-maths-courses.html

• Free Data Analytics Courses

  Wherever your skills are at today, check out these top course recommendations for 2020 to help you master data analytics.

  https://www.kdnuggets.com/2020/06/free-data-analytics-courses.html

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

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

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

• Math and Architectures of Deep Learning

  This hands-on book bridges the gap between theory and practice, showing you the math of deep learning algorithms side by side with an implementation in PyTorch. Save 40% off Math and Architectures of Deep Learning with code nlkdarch40

  https://www.kdnuggets.com/2020/06/manning-math-architectures-deep-learning.html

• Natural Language Processing with Python: The Free eBook">Natural Language Processing with Python: The Free eBook

  This free eBook is an introduction to natural language processing, and to NLTK, one of the most prevalent Python NLP libraries.

  https://www.kdnuggets.com/2020/06/natural-language-processing-python-free-ebook.html

• If you had to start statistics all over again, where would you start?">If you had to start statistics all over again, where would you start?

  If you are just diving into learning statistics, then where do you begin? Find insight from those who have tread in these waters before, and see what they might have done differently along their personal journeys in statistics.

  https://www.kdnuggets.com/2020/06/start-statistics-all-over-again.html

• Privacy-preserving AI – Why do we need it?

  Various data privacy threats can result from the usual process of building and constructing data and AI-based systems. Avoiding these challenges can be supported by utilizing state-of-the-art technologies in the domain of privacy-preserving AI.

  https://www.kdnuggets.com/2020/05/privacy-preserving-ai.html

• The Best NLP with Deep Learning Course is Free">The Best NLP with Deep Learning Course is Free

  Stanford's Natural Language Processing with Deep Learning is one of the most respected courses on the topic that you will find anywhere, and the course materials are freely available online.

  https://www.kdnuggets.com/2020/05/best-nlp-deep-learning-course-free.html

• I Designed My Own Machine Learning and AI Degree

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

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

• Deep Learning: The Free eBook">Deep Learning: The Free eBook

  "Deep Learning" is the quintessential book for understanding deep learning theory, and you can still read it freely online.

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

• Math and Architectures of Deep Learning

  This hands-on book bridges the gap between theory and practice, showing you the math of deep learning algorithms side by side with an implementation in PyTorch. You can save 40% off Math and Architectures of Deep Learning until May 13! Just enter the code nlkdarch40 at checkout when you buy from manning.com.

  https://www.kdnuggets.com/2020/04/manning-math-architectures-deep-learning.html

• The Benefits & Examples of Using Apache Spark with PySpark

  Apache Spark runs fast, offers robust, distributed, fault-tolerant data objects, and integrates beautifully with the world of machine learning and graph analytics. Learn more here.

  https://www.kdnuggets.com/2020/04/benefits-apache-spark-pyspark.html

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

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

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

• Dive Into Deep Learning: The Free eBook

  This freely available text on deep learning is fully interactive and incredibly thorough. Check out "Dive Into Deep Learning" now and increase your neural networks theoretical understanding and practical implementation skills.

  https://www.kdnuggets.com/2020/04/dive-deep-learning-book.html

• Better notebooks through CI: automatically testing documentation for graph machine learning

  In this article, we’ll walk through the detailed and helpful continuous integration (CI) that supports us in keeping StellarGraph’s demos current and informative.

  https://www.kdnuggets.com/2020/04/better-notebooks-through-ci-automatically-testing-documentation-graph-machine-learning.html

• Federated Learning: An Introduction

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

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

• 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

• A Top Machine Learning Algorithm Explained: Support Vector Machines (SVM)">A Top Machine Learning Algorithm Explained: Support Vector Machines (SVM)

  Support Vector Machines (SVMs) are powerful for solving regression and classification problems. You should have this approach in your machine learning arsenal, and this article provides all the mathematics you need to know -- it's not as hard you might think.

  https://www.kdnuggets.com/2020/03/machine-learning-algorithm-svm-explained.html

• Scaling Your Data Strategy

  This article presents a particular vision for a cohesive data strategy for addressing large-scale problems with data-driven solutions, based on prior professional experiences.

  https://www.kdnuggets.com/2020/03/scaling-data-strategy.html

• Skynet Is Real: The History and Future of Factories With No Workers

  Let’s see whether robots will become "grave diggers" of the proletariat, what do we lack to get total automation, and what compromises exist.

  https://www.kdnuggets.com/2020/03/skynet-real-history-future-factories-no-workers.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

• Linear to Logistic Regression, Explained Step by Step">Linear to Logistic Regression, Explained Step by Step

  Logistic Regression is a core supervised learning technique for solving classification problems. This article goes beyond its simple code to first understand the concepts behind the approach, and how it all emerges from the more basic technique of Linear Regression.

  https://www.kdnuggets.com/2020/03/linear-logistic-regression-explained.html

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

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

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

• Decision Tree Intuition: From Concept to Application

  While the use of Decision Trees in machine learning has been around for awhile, the technique remains powerful and popular. This guide first provides an introductory understanding of the method and then shows you how to construct a decision tree, calculate important analysis parameters, and plot the resulting tree.

  https://www.kdnuggets.com/2020/02/decision-tree-intuition.html

• Data Science Curriculum for self-study

  Are you asking the question, "how do I become a Data Scientist?" This list recommends the best essential topics to gain an introductory understanding for getting started in the field. After learning these basics, keep in mind that doing real data science projects through internships or competitions is crucial to acquiring the core skills necessary for the job.

  https://www.kdnuggets.com/2020/02/data-science-curriculum-self-study.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

• Free Mathematics Courses for Data Science & Machine Learning">Free Mathematics Courses for Data Science & Machine Learning

  It's no secret that mathematics is the foundation of data science. Here are a selection of courses to help increase your maths skills to excel in data science, machine learning, and beyond.

  https://www.kdnuggets.com/2020/02/free-mathematics-courses-data-science-machine-learning.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

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

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

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

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

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

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

• 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

• Graph Machine Learning Meets UX: An uncharted love affair

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

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

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

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

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

• 3 common data science career transitions, and how to make them happen

  Breaking into a career in Data Science can depend on where you start. See if you fit into one of these three categories of "newbies," and then find out how to make your professional transition into the field.

  https://www.kdnuggets.com/2020/01/3-common-data-science-career-transitions.html

• Towards a Quantitative Measure of Intelligence: Breaking Down One of the Most Important AI Papers of 2019, Part II

  AI scientist Francois Chollet proposes a better framework for measuring the intelligence of AI systems.

  https://www.kdnuggets.com/2019/12/towards-quantitative-measure-intelligence-important-ai-paper-2019-2.html

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

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

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

• 10 Best and Free Machine Learning Courses, Online

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

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

• Interpretability part 3: opening the black box with LIME and SHAP

  The third part in a series on leveraging techniques to take a look inside the black box of AI, this guide considers methods that try to explain each prediction instead of establishing a global explanation.

  https://www.kdnuggets.com/2019/12/interpretability-part-3-lime-shap.html

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

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

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

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

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

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

• Artificial Friend or Virtual Foe

  Is AI making more good than harm?

  https://www.kdnuggets.com/2019/12/artificial-friend-virtual-foe.html

• Spark NLP 101: LightPipeline

  A Pipeline is specified as a sequence of stages, and each stage is either a Transformer or an Estimator. These stages are run in order, and the input DataFrame is transformed as it passes through each stage. Now let’s see how this can be done in Spark NLP using Annotators and Transformers.

  https://www.kdnuggets.com/2019/11/spark-nlp-101-lightpipeline.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

• What is Machine Learning on Code?

  Not only can MLonCode help companies streamline their codebase and software delivery processes, but it also helps organizations better understand and manage their engineering talents.

  https://www.kdnuggets.com/2019/11/machine-learning-code-mloncode.html

• Introduction to Natural Language Processing (NLP)

  Have you ever wondered how your personal assistant (e.g: Siri) is built? Do you want to build your own? Perfect! Let’s talk about Natural Language Processing.

  https://www.kdnuggets.com/2019/10/introduction-natural-language-processing.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

• Data Preparation for Machine learning 101: Why it’s important and how to do it

  As data scientists who are the brains behind the AI-based innovations, you need to understand the significance of data preparation to achieve the desired level of cognitive capability for your models. Let’s begin.

  https://www.kdnuggets.com/2019/10/data-preparation-machine-learning-101.html