- Cartoon: AI understanding of Coronavirus - Apr 1, 2020.
Here is a cartoon to distract you, showing a new level of understanding AI could reach.
- Want to Build an AI Model for Your Business? Read this - Mar 25, 2020.
The best approach for AI production is similar to what venture capitalists (VC’s) do when they evaluate and invest in startups.
- Top AI Resources – Directory for Remote Learning - Mar 24, 2020.
Whether you are just learning Data Science, a current professional, or just interested, it's crucial to keep the mind stimulated and stay current. With conferences, schools, and travel largely canceled because of #coronavirus, these remote resources will help you stay engaged.
- Unlocking the Potential of FAIR Data Using AI at Roche - Mar 9, 2020.
Learn from the head of the data science department in research and early development at Roche. Use the code KDNUGGETS for a 15% discount on your Predictive Analytics World ticket, 11-12 May in Munich.
- Resources for Women in AI, Data Science, and Machine Learning - Mar 8, 2020.
For the international women's day, we feature resources to help more women enter and succeed in AI, Big Data, Data Science, and Machine Learning fields.
- 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 2) - Mar 2, 2020.
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.
- Prepare for a Long Battle against Deepfakes - Feb 21, 2020.
While deepfakes threaten to destroy our perception of reality, the tech giants are throwing down the gauntlet and working to enhance the state of the art in combating doctored videos and images.
- How Kubeflow Can Add AI to Your Kubernetes Deployments - Feb 21, 2020.
As Kubernetes is capable of working with other solutions, it is possible to integrate it with a collection of tools that can almost fully automate your development pipeline. Some of those third-party tools even allow you to integrate AI into Kubernetes. One such tool you can integrate with Kubernetes is Kubeflow. Read more about it here.
- Hand labeling is the past. The future is #NoLabel AI - Feb 19, 2020.
Data labeling is so hot right now… but could this rapidly emerging market face disruption from a small team at Stanford and the Snorkel open source project, which enables highly efficient programmatic labeling that is 10 to 1,000x as efficient as hand labeling?
- KDnuggets™ News 20:n07, Feb 19: 20 AI, Data Science, Machine Learning Terms for 2020; Why Did I Reject a Data Scientist Job? - Feb 19, 2020.
This week on KDnuggets: 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020; Why Did I Reject a Data Scientist Job?; Fourier Transformation for a Data Scientist; Math for Programmers; Deep Neural Networks; Practical Hyperparameter Optimization; and much more!
- 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 1) - Feb 18, 2020.
2020 is well underway, and we bring you 20 AI, data science, and machine learning terms we should all be familiar with as the year marches onward.
- Using AI to Identify Wildlife in Camera Trap Images from the Serengeti - Feb 17, 2020.
With recent developments in machine learning and computer vision, we acquired the tools to provide the biodiversity community with an ability to tap the potential of the knowledge generated automatically with systems triggered by a combination of heat and motion.
- Top KDnuggets tweets, Feb 05-11: #SciPy 1.0: fundamental algorithms for scientific computing in #Python; Why is Data Science so popular? - Feb 12, 2020.
Why is Data Science so Popular?; Visual Paper Summary: ALBERT (A Lite BERT); Uber Has Assembled One of the Most Impressive Open Source DL Stacks; Top #AI Influencers To Follow in 2020
- AI and Machine Learning In Our Every Day Life - Feb 7, 2020.
The curiosity and buzz around the most talked-about technology -- Artificial Intelligence -- have experts and technophiles busy decoding its exciting future applications. Of course, the use of AI and machine learning is already pervasive in our daily lives, as we review many of these popular features in this article.
- The Data Science Puzzle — 2020 Edition - Feb 7, 2020.
The data science puzzle is once again re-examined through the relationship between several key concepts of the landscape, incorporating updates and observations since last time. Check out the results here.
- The Future of Machine Learning Will Include a Lot Less Engineering - Feb 6, 2020.
Despite getting less attention, the systems-level design and engineering challenges in ML are still very important — creating something useful requires more than building good models, it requires building good systems.
- Intro to Machine Learning and AI based on high school knowledge - Feb 5, 2020.
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.
- Top 5 Data Science Trends for 2020 - Feb 4, 2020.
As Data Science continues to expand into the next decade, this article features five important trends in the field that are expected in 2020. Leverage these trends to help improve your business processes for maximizing growth.
- OpenAI is Adopting PyTorch… They Aren’t Alone - Jan 31, 2020.
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.
- A bird’s-eye view of modern AI from NeurIPS 2019 - Jan 28, 2020.
With the explosion of the field of AI/ML impacting so many applications and industries, there is great value coming out of recent progress. This review highlights many research areas covered at the NeurIPS 2019 conference recently held in Vancouver, Canada, and features many important areas of progress we expect to see in the coming year.
- NLP Year in Review — 2019 - Jan 23, 2020.
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.
- Top 5 AI trends for 2020 - Jan 21, 2020.
We are all witnessing a staggering growth of AI technology with so many new benefits for people while also changing the way we live and work. As AI continues to grow, which applications will have a significant impact in 2020?
- Artificial Intelligence Books to Read in 2020 - Jan 21, 2020.
Here are some AI-related books that I’ve read and recommend for you to add to your 2020 reading list!
- We Created a Lazy AI - Jan 20, 2020.
This article is an overview of how to design and implement reinforcement learning for the real world.
- Top 10 Technology Trends for 2020 - Jan 16, 2020.
With integrations of multiple emerging technologies just in the past year, AI development continues at a fast pace. Following the blueprint of science and technology advancements in 2019, we predict 10 trends we expect to see in 2020 and beyond.
- Disentangling disentanglement: Ideas from NeurIPS 2019 - Jan 15, 2020.
This year’s NEURIPS-2019 Vancouver conference recently concluded and featured a dozen papers on disentanglement in deep learning. What is this idea and why is it so interesting in machine learning? This summary of these papers will give you initial insight in disentanglement as well as ideas on what you can explore next.
- 7 AI Use Cases Transforming Live Sports Production and Distribution - Jan 14, 2020.
Here are 7 powerful AI led use cases both for linear television and for OTT apps that are transforming the live sports production landscape.
- Deepfakes Security Risks - Jan 10, 2020.
Deepfakes have instilled panic in experts since they first emerged in 2017. Microsoft and Facebook have recently announced a contest to identify deepfakes more efficiently.
- 5 Ways AI Is Changing The Healthcare Industry - Jan 7, 2020.
The healthcare AI market is expected to reach 28 billion dollars by the year 2025. With such exponential growth, AI is undoubtedly likely to bring some drastic changes in the healthcare industry. Let’s look at five ways of how AI has changed the healthcare industry.
- Cartoon: Teaching Ethics to AI - Jan 4, 2020.
Ethics in AI has received significant attention recently, and the new KDnuggets cartoon examines the problem of teaching ethics to artificially intelligent entities.
- Towards a Quantitative Measure of Intelligence: Breaking Down One of the Most Important AI Papers of 2019, Part II - Dec 31, 2019.
AI scientist Francois Chollet proposes a better framework for measuring the intelligence of AI systems.
- Towards a Quantitative Measure of Intelligence: Breaking Down One of the Most Important AI Papers of 2019, Part I - Dec 30, 2019.
AI scientist Francois Chollet proposes a better framework for measuring the intelligence of AI systems.
- Google’s New Explainable AI Service - Dec 20, 2019.
Google has started offering a new service for “explainable AI” or XAI, as it is fashionably called. Presently offered tools are modest, but the intent is in the right direction.
- Xavier Amatriain’s Machine Learning and Artificial Intelligence 2019 Year-end Roundup - Dec 16, 2019.
It is an annual tradition for Xavier Amatriain to write a year-end retrospective of advances in AI/ML, and this year is no different. Gain an understanding of the important developments of the past year, as well as insights into what expect in 2020.
- What just happened in the world of AI? - Dec 12, 2019.
The speed at which AI made advancements and news during 2019 makes it imperative now to step back and place these events into order and perspective. It's important to separate the interest that any one advancement initially attracts, from its actual gravity and its consequential influence on the field. This review unfolds the parallel threads of these AI stories over this year and isolates their significance.
- AI, Analytics, Machine Learning, Data Science, Deep Learning Technology Main Developments in 2019 and Key Trends for 2020 - Dec 11, 2019.
We asked leading experts - what are the most important developments of 2019 and 2020 key trends in AI, Analytics, Machine Learning, Data Science, and Deep Learning? This blog focuses mainly on technology and deployment.
- AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2019 and Key Trends for 2020 - Dec 9, 2019.
As we say goodbye to one year and look forward to another, KDnuggets has once again solicited opinions from numerous research & technology experts as to the most important developments of 2019 and their 2020 key trend predictions.
- Accuracy Fallacy: The Media’s Coverage of AI Is Bogus - Dec 6, 2019.
Such as the gross exaggerations Stanford researchers broadcasted about their infamous "AI gaydar" project, there exists a prevalent "accuracy fallacy" in relation to AI from the media. Find out more about how the press constantly misleads the public into believing that machine learning can reliably predict psychosis, heart attacks, sexuality, and much more.
- Artificial Friend or Virtual Foe - Dec 5, 2019.
Is AI making more good than harm?
- Top 7 Data Science Use Cases in Trust and Security - Dec 2, 2019.
What are trust and safety? What is the role of trust and security in the modern world? Read this overview of 7 data science application use cases in the realm of trust and security.
- Two Years In The Life of AI, Machine Learning, Deep Learning and Java - Nov 29, 2019.
Where does Java stand in the world of artificial intelligence, machine learning, and deep learning? Learn more about how to do these things in Java, and the libraries and frameworks to use.
- Open Source Projects by Google, Uber and Facebook for Data Science and AI - Nov 28, 2019.
Open source is becoming the standard for sharing and improving technology. Some of the largest organizations in the world namely: Google, Facebook and Uber are open sourcing their own technologies that they use in their workflow to the public.
- On the sensationalism of artificial intelligence news - Nov 15, 2019.
With artificial intelligence and machine learning now a mainstay of our daily awareness, news organizations have been seen to overstate the reality behind progress in the field. Learn more about recent examples of media hyperbole and explore why this may be happening.
- AI ROI: The Questions You Need To Be Asking - Nov 14, 2019.
During this free Metis Corporate Training webinar, Dec 5 @ 12pm ET, Kerstin Frailey, Senior Data Scientist and Head of Executive Corporate Training at Metis, will walk through what you need to ask before, during, and after the lifetime of a data science project to accurately assess its impact on the business.
- The Last Defense Against Another AI Winter - Nov 6, 2019.
My short answer is this: Yes, another AI Winter will be here if you don’t deploy more ML solutions. You and your Data Science teams are the last line of defense against the AI Winter. You need to solve five key challenges to keep the momentum up.
- KDnuggets™ News 19:n42, Nov 6: 5 Statistical Traps Data Scientists Should Avoid; 10 Free Must-Read Books on AI - Nov 6, 2019.
Learn about statistical fallacies Data Scientists should avoid; New and quite amazing Deep Learning capabilities FB has been quietly open-sourcing; Top Machine Learning tools for Developers; How to build a Neural Network from scratch and more.
- 10 Free Must-read Books on AI - Nov 5, 2019.
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.
- How Data Labeling Facilitates AI Models - Oct 31, 2019.
AI-based models are highly dependent on accurate, clean, well-labeled, and prepared data in order to produce the desired output and cognition. These models are fed with bulky datasets covering an array of probabilities and computations to make its functioning as smart and gifted as human intelligence.
- About Google’s Self-Proclaimed Quantum Supremacy and its Impact on Artificial Intelligence - Oct 29, 2019.
Google claimed quantum supremacy, IBM challenged it… but the development is really important for the future of AI.
- Harnessing Semiotics and Discourse Communities to Understand User Intent - Oct 25, 2019.
Semiotics helps us understand the importance of context to determining the meaning of a term and discourse communities provide us with the background context (mental model) by which to correctly interpret its meaning correctly.
- Seven Myths About the True Costs of AI Systems - Oct 24, 2019.
While there is much excitement today around implementing AI at the enterprise level, the financial costs of this process are often unexpected and underappreciated. These seven myths are crucial lessons learned that executives should know before heading down the road to AI.
- Samsung Tech Day: Today’s Electronic Devices Seem Magical, But the Real Super-Power is in Silicon - Oct 23, 2019.
Samsung’s Tech Day event showcases processor and memory advances for 5G, AI, Cloud and Edge Computing, Automotive, IoT, and more.
- Intro to Adversarial Machine Learning and Generative Adversarial Networks - Oct 23, 2019.
In this crash course on GANs, we explore where they fit into the pantheon of generative models, how they've changed over time, and what the future has in store for this area of machine learning.
- KDnuggets™ News 19:n40, Oct 23: How to Become a (Good) Data Scientist; Writing Your First Neural Net in 30 Lines with Keras - Oct 23, 2019.
Read useful advice on how to become a good data scientist; see how you can write your 1st neural net in under 30 lines of Keras code; Understand why AI salaries are heading skywards and what skills you need for them; and read about key ideas and methods in anomaly detection
- Bye Data Scientists, Hello AI? Not Likely! - Oct 22, 2019.
AI is becoming more mainstream. The fact that computers/robots will learn after being built and will surpass a human's intelligence is terrifying.
- Anomaly Detection, A Key Task for AI and Machine Learning, Explained - Oct 21, 2019.
One way to process data faster and more efficiently is to detect abnormal events, changes or shifts in datasets. Anomaly detection refers to identification of items or events that do not conform to an expected pattern or to other items in a dataset that are usually undetectable by a human expert.
- Building an intelligent Digital Assistant - Oct 18, 2019.
In this second part we want to outline our own experience building an AI application and reflect on why we chose not to utilise deep learning as the core technology used.
- Artificial Intelligence: Salaries Heading Skyward - Oct 17, 2019.
While the average salary for a Software Engineer is around $100,000 to $150,000, to make the big bucks you want to be an AI or Machine Learning (Specialist/Scientist/Engineer.)
- KDnuggets™ News 19:n39, Oct 16: Key Ideas in Document Embedding; The problem with metrics is a big problem for AI - Oct 16, 2019.
This week on KDnuggets: Beyond Word Embedding: Key Ideas in Document Embedding; The problem with metrics is a big problem for AI; Activation maps for deep learning models in a few lines of code; There is No Such Thing as a Free Lunch; 8 Paths to Getting a Machine Learning Job Interview; and much, much more.
- There is No Such Thing as a Free Lunch - Oct 11, 2019.
You have heard the expression “there is no such thing as a free lunch” – well in machine learning the same principle holds. In fact there is even a theorem with the same name.
- The problem with metrics is a big problem for AI - Oct 11, 2019.
The practice of optimizing metrics is not new nor unique to AI, yet AI can be particularly efficient (even too efficient!) at doing so.
- Lemma, Lemma, Red Pyjama: Or, doing words with AI - Oct 10, 2019.
If we want a machine learning model to be able to generalize these forms together, we need to map them to a shared representation. But when are two different words the same for our purposes? It depends.
- Why the ‘why way’ is the right way to restoring trust in AI - Oct 8, 2019.
As so many more organizations now rely on AI to deliver services and consumer experiences, establishing a public trust in the AI is crucial as these systems begin to make harder decisions that impact customers.
- OpenAI Tried to Train AI Agents to Play Hide-And-Seek but Instead They Were Shocked by What They Learned - Oct 7, 2019.
OpenAI trained agents in a simple game of hide-and-seek and learned many other different skills in the process.
- 5 Fundamental AI Principles - Oct 3, 2019.
While AI may appear magical at times, these five principles will help guide you to avoid pitfalls when leveraging this tech.
- How AI will transform healthcare (and can it fix the US healthcare system?) - Sep 30, 2019.
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.
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- KDnuggets™ News 19:n36, Sep 25: The Hidden Risk of AI and Big Data; The 5 Sampling Algorithms every Data Scientist needs to know - Sep 25, 2019.
Learn about unexpected risk of AI applied to Big Data; Study 5 Sampling Algorithms every Data Scientist needs to know; Read how one data scientist copes with his boring days of deploying machine learning; 5 beginner-friendly steps to learn ML with Python; and more.
- 5 Famous Deep Learning Courses/Schools of 2019 - Sep 24, 2019.
Deep Learning is/has become the hottest skill in Data Science at the moment. There is a plethora of articles, courses, technologies, influencers and resources that we can leverage to gain the Deep Learning skills.
- The Hidden Risk of AI and Big Data - Sep 20, 2019.
With recent advances in AI being enabled through access to so much “Big Data” and cheap computing power, there is incredible momentum in the field. Can big data really deliver on all this hype, and what can go wrong?
- What is Machine Behavior? - Sep 16, 2019.
The new emerging field that wants to study AI agents the way social scientists study humans.
- Top KDnuggets tweets, Sep 04-10: How #AI will transform #healthcare; 10 Great Python Resources for Aspiring Data Scientists - Sep 11, 2019.
Python Libraries for Interpretable Machine Learning; How #AI will transform #healthcare (and can it fix US healthcare system?); Building Recommendation System - an overview ; I wasn't getting hired as a Data Scientist. So I sought data on who is.
- BERT is changing the NLP landscape - Sep 9, 2019.
BERT is changing the NLP landscape and making chatbots much smarter by enabling computers to better understand speech and respond intelligently in real-time.
- Beyond Neurons: Five Cognitive Functions of the Human Brain that we are Trying to Recreate with Artificial Intelligence - Sep 3, 2019.
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.
- Cartoon: Labor Day in the age of AI - Sep 2, 2019.
KDnuggets cartoon looks at how AI will impact Labor Day in the year 2050.
- The Death of Centralized AI and the Rise of Open AI - Aug 29, 2019.
Centralized AI is giving way to more democratic AI systems, which are becoming more and more accessible to data scientists, both through code and through open ecosystems.
- A 2019 Guide to Human Pose Estimation - Aug 28, 2019.
Human pose estimation refers to the process of inferring poses in an image. Essentially, it entails predicting the positions of a person’s joints in an image or video. This problem is also sometimes referred to as the localization of human joints.
- Introducing AI Explainability 360: A New Toolkit to Help You Understand what Machine Learning Models are Doing - Aug 27, 2019.
Recently, AI researchers from IBM open sourced AI Explainability 360, a new toolkit of state-of-the-art algorithms that support the interpretability and explainability of machine learning models.
- Artificial Intelligence vs. Machine Learning vs. Deep Learning: What is the Difference? - Aug 26, 2019.
Over the past few years, artificial intelligence continues to be one of the hottest topics. And in order to work effectively with it, you need to understand its constituent parts.
- Gender Diversity in AI Research - Aug 21, 2019.
Through an analysis of 1.5M papers from arXiv, this study reviews the evolution of gender diversity across disciplines, countries, and institutions as well as the semantic differences between AI papers with and without female co-authors.
- Artificial Intelligence Is Not Intelligence – Interview With Andy Cotgreave (Keynote Speaker at Crunch Conf) - Aug 20, 2019.
Crunch is coming to Budapest, Hungary on 16-18 Oct. Use code KDNuggets to save on Data Science, Data Engineering, or BI tracks. But first, read this interview with keynote speaker Andy Cotgreave.
- U. of Miami: Faculty Positions, with expertise in AI/Data Science/ML or related areas [Miami, FL] - Aug 15, 2019.
The positions require research and teaching expertise in AI/Data Science, or related areas including Data Extraction, Data Visualization, Machine Learning, and Intelligent Actuators.
- Introducing the Plato Research Dialogue System: Building Conversational Applications at Uber’s Scale - Aug 15, 2019.
While the process of building simple, domain-specific chatbots has gotten way easier, building large scale, multi-agent conversational applications remains a massive challenge. Recently, the Uber engineering team open sourced the Plato Research Dialogue System, which is the framework powering conversational agents across Uber’s different applications.
- How Creating an AI Study Group Boosted My Skills and Got Me a Job - Aug 13, 2019.
The amount of time I had to put in to organize the AI Society left me sometimes sleep-deprived but it was definitely worth it. It was also one of the main factors why I got the job in Machine Learning after all. I hope that this article will inspire you to create your own AI study group!
- 6 Key Concepts in Andrew Ng’s “Machine Learning Yearning” - Aug 12, 2019.
If you are diving into AI and machine learning, Andrew Ng's book is a great place to start. Learn about six important concepts covered to better understand how to use these tools from one of the field's best practitioners and teachers.
- Inside Pluribus: Facebook’s New AI That Just Mastered the World’s Most Difficult Poker Game - Aug 8, 2019.
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.
- Are We Ready to Partner With Machines?
Data Science Salon Miami, September 10-11 - Jul 31, 2019.
When it comes to AI, there’s plenty of talk of the future of machines. But it’s the people behind AI development who have the insights needed to shape that future. Register now to catch all of our speakers at the Data Science Salon Miami, Sep 10-11, 2019.
- Top 10 Best Podcasts on AI, Analytics, Data Science, Machine Learning - Jul 29, 2019.
Check out our latest Top 10 Most Popular Data Science and Machine Learning podcasts available on iTunes. Stay up to date in the field with these recent episodes and join in with the current data conversations.
- Decentralized and Collaborative AI: How Microsoft Research is Using Blockchains to Build More Transparent Machine Learning Models - Jul 29, 2019.
Recently, AI researchers from Microsoft open sourced the Decentralized & Collaborative AI on Blockchain project that enables the implementation of decentralized machine learning models based on blockchain technologies.
- High-Quality AI And Machine Learning Data Labeling At Scale: A Brief Research Report - Jul 25, 2019.
Analyst firm Cognilytica estimates that as much as 80% of machine learning project time is spent on aggregating, cleaning, labeling, and augmenting machine learning model data. So, how do innovative machine learning teams prepare data in such a way that they can trust its quality, cost of preparation, and the speed with which it’s delivered?
- State of AI Report 2019 - Jul 5, 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.
- NLP vs. NLU: from Understanding a Language to Its Processing - Jul 3, 2019.
As AI progresses and the technology becomes more sophisticated, we expect existing techniques to evolve. With these changes, will the well-founded natural language processing give way to natural language understanding? Or, are the two concepts subtly distinct to hold their own niche in AI?
- Seven Key Dimensions to Help You Understand Artificial Intelligence Environments - Jul 2, 2019.
Understanding an AI environment is an incredibly complex task but there are several key dimensions that provide clarity on that reasoning.
- How To Get Funding For AI Startups - Jun 27, 2019.
What are the biggest challenges AI startups have when pitching to investors? Learn how to grab their attention with these recommendations on how to start building your AI company.
- Monash University: (Senior) Research Fellow in AI [Suzhou, China] - Jun 26, 2019.
Seeking an individual passionate about undertaking research in an area of Artificial Intelligence (AI), as well as multidisciplinary research through the application of AI to problems, and to be responsible for conducting research in areas of AI.
- How Google uses Reinforcement Learning to Train AI Agents in the Most Popular Sport in the World - Jun 21, 2019.
Researchers from the Google Brain team open sourced Google Research Football, a new environment that leverages reinforcement learning to teach AI agents how to master the most popular sport in the world.
- Natural Language Interface to DataTable - Jun 21, 2019.
You have to write SQL queries to query data from a relational database. Sometimes, you even have to write complex queries to do that. Won't it be amazing if you could use a chatbot to retrieve data from a database using simple English? That's what this tutorial is all about.
- Examining the Transformer Architecture: The OpenAI GPT-2 Controversy - Jun 20, 2019.
GPT-2 is a generative model, created by OpenAI, trained on 40GB of Internet to predict the next word. And OpenAI found this model to be SO good that they did not release the fully trained model due to their concerns about malicious applications of the technology.
- The Emergence of Cooperative and Competitive AI Agents - Jun 19, 2019.
Without specific training in collaboration or competition, a recent AI model from DeepMind uses reinforcement learning to evolve these behaviors in game-playing agents. Learn how this emergent collective intelligence outperforms their human counterparts in 3D multiplayer games.
- Penn State: Nittany AI Associates Program Manager [University Park, PA] - Jun 13, 2019.
Seeking an individual who can contribute to the overall success of the program by providing input and direction regarding program goals and operations, and provide leadership and management needed to achieve program success.
- Crowdsourcing vs. Managed Teams: A Study in Data Labeling Quality - Jun 12, 2019.
You need data labeled for ML. You can do it in-house, crowdsource it, or hire a managed service. If data quality matters, read this.
- Why organizations fail in scaling AI and Machine Learning - May 29, 2019.
We explain why AI needs to understand business processes and how the business processes need to be able to change to bring insight from AI into the process.
- Big Data and AI Toronto 2019 - May 28, 2019.
Don't miss Canada's #1 data, AI and analytics conference + expo. From solving your data-driven business challenges to helping you navigate the latest machine learning tools, Big Data and AI Toronto is designed to give you a 360-degree view on the industry.
- AI in the Family: how to teach machine learning to your kids - May 28, 2019.
AI is all the rage with today’s programmers, but what about the next generation? Machine learning can be introduced to young ones just now learning about code, and you can help spark their interest.
- Your Guide to Natural Language Processing (NLP) - May 23, 2019.
This extensive post covers NLP use cases, basic examples, Tokenization, Stop Words Removal, Stemming, Lemmatization, Topic Modeling, the future of NLP, and more.
- Building a Computer Vision Model: Approaches and datasets - May 20, 2019.
How can we build a computer vision model using CNNs? What are existing datasets? And what are approaches to train the model? This article provides an answer to these essential questions when trying to understand the most important concepts of computer vision.
- Think Like an Amateur, Do As an Expert: Lessons from a Career in Computer Vision - May 17, 2019.
Dr. Takeo Kanade shared his life lessons from an illustrious 50-year career in Computer Vision at last year's Embedded Vision Summit. You have a chance to attend the 2019 Embedded Vision Summit, from May 20-23, in the Santa Clara Convention Center, Santa Clara CA.
- Machine Learning in Agriculture: Applications and Techniques - May 14, 2019.
Machine Learning has emerged together with big data technologies and high-performance computing to create new opportunities to unravel, quantify, and understand data intensive processes in agricultural operational environments.
- What’s Going to Happen this Year in the Data World - May 14, 2019.
"If we wish to foresee the future of mathematics, our proper course is to study the history and present condition of the science." Henri Poncairé.
- Ethical AI: EU’s New Guidelines and the Future of AI Trustworthiness - May 10, 2019.
The EU has issued a set of guidelines, "Ethics Guidelines for Trustworthy AI" to help tech companies steer towards ethical and inclusive AI as we come to terms with the potential of this technology.
- Monash U.: Lecturer/Senior Lecturer (Creative AI) [Melbourne, Australia] - May 9, 2019.
Monash University is seeking a (Senior) Lecturer in Creative AI, to join our high achieving and highly motivated team of teaching and research staff. Apply by 19 May 2019.
- Strata SF day 2 Highlights: AI and Politics, Chatbots Insights, Forecasting Uncertainty, Scalable Video Analysis, and more - May 3, 2019.
AI influencing Politics, insights from Chatbots, Enterprise Data Cloud, handling Video Big Data, and more takeaways from Strata Data Conference 2019, San Francisco.
- Strata SF day 1 Highlights: from Edge to AI, scoring AI projects, cyberconflict, cryptography - Apr 29, 2019.
Journey from “Edge to AI”, scoring your AI projects, cyberconflict, role of cryptography in AI and more insights from a leading conference.
- Delivering Trusted AI with DataRobot and Microsoft - Apr 26, 2019.
In this webinar, Apr 30 @ 1 PM ET, attendees will learn more about how their organizations can add AI to BI, making more predictive decisions along the way.
- AI and the data production landscape - Apr 26, 2019.
Data Science Salon NY returns to Viacom HQ in Times Square on June 13. Here are insights from DSS NY top speakers on the future of AI in the media production landscape.
- Meet the World’s Leading AI & Deep Learning Experts - Apr 25, 2019.
RE-WORK returns to San Francisco Jun 20-21 with the Deep Reinforcement Learning Summit, the Applied AI Summit and the AI for Good Summit. KDnuggets subscribers get 20% off Early Bird discounted passes when you register before May 3 with code KDNUGGETS.
- Attention Craving RNNS: Building Up To Transformer Networks - Apr 24, 2019.
RNNs let us model sequences in neural networks. While there are other ways of modeling sequences, RNNs are particularly useful. RNNs come in two flavors, LSTMs (Hochreiter et al, 1997) and GRUs (Cho et al, 2014)
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- AI Supporting The Earth - Apr 22, 2019.
To celebrate Earth Day 2019, we explain how Intel is committed to advancing uses of AI that positively impact our world by providing social good organizations with technologies and expertise to accelerate their work.
- Distributed Artificial Intelligence: A primer on Multi-Agent Systems, Agent-Based Modeling, and Swarm Intelligence - Apr 18, 2019.
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.
- An introduction to explainable AI, and why we need it - Apr 15, 2019.
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.
- AI For Ordinary Folks - Apr 11, 2019.
There are many excellent books, articles, YouTube lectures and blogs on AI and topics related to it aimed at data scientists and AI researchers. You may want to, instead, check out this list of AI resources crafted for ordinary folks.
- [Upcoming Webinar] 5 Steps to Building Responsible AI Systems - Apr 10, 2019.
What does responsible AI mean? This webinar, Apr 18 @ 11 AM ET, will cover the essential steps to building AI systems that are responsible.
- Beyond Siri, Google Assistant, and Alexa – what you need to know about AI Conversational Applications - Apr 10, 2019.
We discuss industry trends in Artificial Intelligence with Vijay Ramakrishnan, a machine learning engineer and expert in conversational applications.
- What is missing when AI makes a decision? - Apr 5, 2019.
We explain the need for caution when it comes to using AI in real-life situations and outline the importance of asking the right question to deliver the right impact.
- Another 10 Free Must-See Courses for Machine Learning and Data Science - Apr 5, 2019.
Check out another follow-up collection of free machine learning and data science courses to give you some spring study ideas.
- Download your DATAx guide to AI in Marketing - Apr 4, 2019.
Find out how marketers can utilise AI, data segmentation, digital natives, influencers, apps and the internet to help build better, more personalized customer experience: download our ebook 'DATAx: Guide to AI in Marketing'.
- KDnuggets Offer: Save 20% on Strata in London - Apr 4, 2019.
Strata Data Conference is coming to London Apr 29-May 2. Discover what's coming in data and AI. Save 20% on Gold, Silver, and Bronze passes with code KDNU (up to £231 on a Gold pass).
- Accelerate AI and Data Science Career Expo, May 4, 2019 - Apr 3, 2019.
The Accelerate AI and Data Science Career Expo 2019 takes place Saturday, May 4th from 10:30am - 3:00pm. Get your ticket now, or join us for free as an ODSC ticket holder!
- Yeshiva University: Tenure-track Faculty in AI and Machine Learning (Open Rank) [New York, NY] - Apr 2, 2019.
The Katz School of Science and Health at Yeshiva University invites applications for tenure-track faculty in Artificial Intelligence, Machine Learning and Computer Science for its graduate programs.
- Yeshiva University: Program Director / Tenure Track Faculty Member of Artificial Intelligence and Machine Learning [New York, NY] - Apr 2, 2019.
The Katz School of Science and Health at Yeshiva University seeks a dynamic leader to serve as academic and administrative head of its graduate initiatives in Artificial Intelligence and Machine Learning. This is a tenure eligible position depending on experience and qualifications.
- XAI – A Data Scientist’s Mouthpiece - Apr 1, 2019.
We outline the usefulness of Explainable AI, which allows you to explain the results of a multidimensional model - including having a multimodal decision boundary - to a business user.