- Largest Dataset Analyzed – Poll Results and Trends - Jul 1, 2020.
The results show that despite the deluge of Big Data, large majority still works in Gigabyte or Megabyte-size datasets. Data Scientists work with the largest-size datasets, followed by Data Engineers, Data Analysts, and Business Analysts. Read more for details.
- The Unreasonable Progress of Deep Neural Networks in Natural Language Processing (NLP) - Jun 29, 2020.
Natural language processing has made incredible advances through advanced techniques in deep learning. Learn about these powerful models, and find how close (or far away) these approaches are to human-level understanding.
- Will Machine Learning Engineers Exist in 10 Years? - May 8, 2020.
As can be common in many technical fields, the landscape of specialized roles is evolving quickly. With more people learning at least a little machine learning, this could eventually become a common skill set for every software engineer.
- Coronavirus Trends – what can we learn - Mar 31, 2020.
We examine the coronavirus trends, and look at death rates from Covid-19, including absolute numbers, adjusted for population, and daily change rates. The daily change rates are declining for almost all countries, including Italy and Spain, but remaining alarmingly high for US and especially New York State.
- When Will AutoML replace Data Scientists? Poll Results and Analysis - Mar 16, 2020.
Will AI always be 5-10 years away? The majority of respondents to this poll think that AutoML will reach expert level in 5-10 years. Interestingly, it is about the same as 5 years ago. We examine the trends by AutoML experience, industry, and region.
- Trends in Machine Learning in 2020 - Mar 5, 2020.
Many industries realize the potential of Machine Learning and are incorporating it as a core technology. Progress and new applications of these tools are moving quickly in the field, and we discuss expected upcoming trends in Machine Learning for 2020.
- 7 Data Trends for 2020 (and one non-trend) - Feb 24, 2020.
This article discusses trends that will (and won't) take shape in 2020.
- 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.
- The Death of Data Scientists – will AutoML replace them? - Feb 20, 2020.
Soon after tech giants Google and Microsoft introduced their AutoML services to the world, the popularity and interest in these services skyrocketed. We first review AutoML, compare the platforms available, and then test them out against real data scientists to answer the question: will AutoML replace us?
- 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.
- Top 10 AI, Machine Learning Research Articles to know - Jan 30, 2020.
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.
- 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.
- The Decade of Data Science - Jan 27, 2020.
With the last decade being so strong for the emerging field of Data Science, this review considers current trends in the industry, popular frameworks, helpful tools, and new tools that can be leveraged more in the future.
- KDnuggets™ News 20:n03, Jan 22: I wanna be a data scientist, but… how? Top 10 Technology Trends for 2020 - Jan 22, 2020.
If you want to be a Data Scientist, but not sure how to start - there is a perfect blog for you; Baidu top 10 technology trends for 2020; Math for programmers!; The future of Machine Learning; and more.
- 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?
- Industry AI, Analytics, Machine Learning, Data Science Predictions for 2020 - Dec 16, 2019.
Predictions for 2020 from a dozen innovative companies in AI, Analytics, Machine Learning, Data Science, and Data industry.
- 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.
- The 4 Hottest Trends in Data Science for 2020 - Dec 9, 2019.
The field of Data Science is growing with new capabilities and reach into every industry. With digital transformations occurring in organizations around the world, 2019 included trends of more companies leveraging more data to make better decisions. Check out these next trends in Data Science expected to take off in 2020.
- Beyond Word Embedding: Key Ideas in Document Embedding - Oct 11, 2019.
This literature review on document embedding techniques thoroughly covers the many ways practitioners develop rich vector representations of text -- from single sentences to entire books.
- The Future of Analytics and Data Science - Sep 26, 2019.
Learn about the current and future issues of data science and possible solutions from this interview with IADSS Co-founder, Dr. Usama Fayyad following his keynote speech at ODSC Boston 2019.
- Getting to the Future First: How Social Data is Transforming Trend Discovery - Sep 23, 2019.
Register now for this webinar, Sep 25 @ 12 PM ET, for a clear approach on how to apply machine learning language technology to massive, unstructured data sets in order to create predictive models of what may be the next “it” ingredient, color, flavor or pack size.
- AI: Arms Race 2.0 - Mar 12, 2019.
An analysis of the current state of the competition between US, Europe, and China in AI, examining research, patent publications, global datasphere, devices and IoT, people, and more.
- Most impactful AI trends of 2018: The rise of ML Engineering - Mar 1, 2019.
As both research and applied teams are doubling down on their engineering and infrastructure needs, the nascent field of ML Engineering will build upon 2018’s foundation and truly blossom in 2019.
- Reflections on the State of AI: 2018 - Feb 26, 2019.
We provide a detailed overview of the key developments in the AI space, focusing on key players, applications, opportunities, and challenges.
- Artificial Intelligence and Data Science Advances in 2018 and Trends for 2019 - Feb 18, 2019.
We recap some of the major highlights in data science and AI throughout 2018, before looking at the some of the potential newest trends and technological advances for the year ahead.
Pages: 1 2
- Top 10 Technology Trends of 2019 - Feb 7, 2019.
This article outlines 10 top trending technologies for 2019, a list which covers diverse topics such as security, IoT, reinforcement learning, energy sustainability, smart cities, and much more.
- Trending Deep Learning Github Repositories - Feb 1, 2019.
Check these pair of resources for trending and top GitHub deep learning repositories for some new ideas on what to be looking out for.
- What were the most significant machine learning/AI advances in 2018? - Jan 22, 2019.
2018 was an exciting year for Machine Learning and AI. We saw “smarter” AI, real-world applications, improvements in underlying algorithms and a greater discussion on the impact of AI on human civilization. In this post, we discuss some of the highlights.
- Webinar: 2019 AI Trends: Filtering the Noise - Jan 18, 2019.
Check out Dataiku's exclusive webinar on Feb 7, 11am EST, "2019 AI Trends: Filtering the Noise," featuring insights from Léo Drefus-Schmidt, Lead Data Scientist at Dataiku.
- State of Deep Learning and Major Advances: H2 2018 Review - Dec 13, 2018.
In this post we summarise some of the key developments in deep learning in the second half of 2018, before briefly discussing the road ahead for the deep learning community.
- KDnuggets™ News 18:n47, Dec 12: Common mistakes when doing machine learning; Here are the most popular Python IDEs / Editors - Dec 12, 2018.
Common mistakes when carrying out machine learning and data science; Most popular Python IDEs/Editors; Machine Learning / AI Main Developments in 2018 and Key Trends for 2019; Machine Learning Project checklist.
- Should you become a data scientist? - Dec 10, 2018.
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.
- DATAx Presents: AI AND MACHINE LEARNING TRENDS IN 2019 - Dec 6, 2018.
This free Ebook from DATAx offers advice on using AI and machine learning to enhance customer satisfaction, how chief data officers are taking the reins on AI strategy, successful case studies from across the business, and more.
- AI, Data Science, Analytics Main Developments in 2018 and Key Trends for 2019 - Dec 3, 2018.
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.
- Latest Trends in Computer Vision Technology and Applications - Nov 7, 2018.
We investigate the advancements in deep learning, the rise of edge computing, object recognition with point cloud, VR and AR enhanced merged reality, semantic instance segmentation and more.
- Diversity in Data Science: Overview and Strategy - Sep 24, 2018.
We take a hard look at diversity within the tech industry, root causes, and potential solutions and highlight resources/initiatives that can connect readers with programs aiding their professional development.
- 10 Big Data Trends You Should Know - Sep 17, 2018.
A collection of Big Data trends to familiarize yourself with, covering IoT Networks, Artificial Intelligence, Predictive Analytics, Dark Data and more.
- Data science of the connected vehicle: perspectives, applications and trends - Jul 9, 2018.
The application of data science to streaming data from vehicles is an emerging field. Here we review general trends and some specific examples of relevant data feeds and applications where data science can deliver value.
- Why a Professional Association for Data Scientists is a Bad Idea - Jul 2, 2018.
This post presents the argument against having a professional association for data scientists.
- The Future of Artificial Intelligence: Is Your Job Under Threat? - Jun 1, 2018.
This article examines the rapid growth of artificial intelligence: how we got to this point, the future AI job market and what can be done.
- Python eats away at R: Top Software for Analytics, Data Science, Machine Learning in 2018: Trends and Analysis - May 22, 2018.
Python continues to eat away at R, RapidMiner gains, SQL is steady, Tensorflow advances pulling along Keras, Hadoop drops, Data Science platforms consolidate, and more.
Pages: 1 2
- KDnuggets™ News 18:n16, Apr 18: Key Algorithms and Statistical Models; Don’t learn Machine Learning in 24 hours; Data Scientist among the best US Jobs in 2018 - Apr 18, 2018.
Also: Top 10 Technology Trends of 2018; 12 Useful Things to Know About Machine Learning; Robust Word2Vec Models with Gensim & Applying Word2Vec Features for Machine Learning Tasks; Understanding What is Behind Sentiment Analysis - Part 1; Getting Started with PyTorch
- Top 10 Technology Trends of 2018 - Apr 13, 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.
- Top 20 Deep Learning Papers, 2018 Edition - Apr 3, 2018.
Deep Learning is constantly evolving at a fast pace. New techniques, tools and implementations are changing the field of Machine Learning and bringing excellent results.
- Four Broken Systems & Four Tech Trends for 2018 - Mar 1, 2018.
We may be well into 2018, but here are a set of tech trends for looking forward, along with a set of 4 systems that manifested how inappropriate, inaccurate or outright broken they are in 2017.
- Resurgence of AI During 1983-2010 - Feb 16, 2018.
We discuss supervised learning, unsupervised learning and reinforcement learning, neural networks, and 6 reasons that helped AI Research and Development to move ahead.
- Which Machine Learning Algorithm be used in year 2118? - Feb 9, 2018.
So what were the answers popping in your head ? Random forest, SVM, K means, Knn or even Deep Learning? No, for the answer, we turn to Lindy Effect.
- Future Trends in Biometrics - Feb 5, 2018.
Biometric identification is moving from the realm of high -tech movie scenes to everyday use. The science is already changing physical and cyber security.
- 2018 Data Science Salary Survey Report - Jan 31, 2018.
Throughout 2017, we conducted an online salary survey open to a range of data science professionals in order to capture data to help us better understand the market.
- KDnuggets™ News 18:n05, Jan 31: Feynman Technique to become a Data Scientist; 4 Big Data Trends for 2018; Data Scientist – best job in America - Jan 31, 2018.
Also How To Grow As A Data Scientist; A Beginner Guide to Data Engineering; Exclusive Interview: Doug Laney on Big Data and Infonomics
- Data Scientist – best job in America, 3 years in a row - Jan 29, 2018.
For the third year in a row, Data Scientist was ranked as the no. 1 job in America by Glassdoor.
- 5 Key Data Science Job Market Trends - Jan 26, 2018.
As a data scientist — or someone interested in the field — you know the industry is constantly evolving. If you want to remain competitive, you need to keep up with popular trends.
- Four Big Data Trends for 2018 - Jan 25, 2018.
Curious about the future of Big Data and AI? Here’s what the trends have it in 2018 for innovations.
- Data Science in 30 minutes, Artificial General Intelligence, and Answers to your Questions - Jan 22, 2018.
I recently was on a "Data Science in 30 minutes webcast", but there were interesting ideas and questions we did not have time to cover adequately. Here is a summary.
- Data Science in 30 Minutes: A Conversation with Gregory Piatetsky-Shapiro, President of KDnuggets - Jan 3, 2018.
KDnuggets founder, Gregory Piatetsky-Shapiro, joins Michael Li, CEO and founder of The Data Incubator, Jan 11 at 2:30 pm PT/ 5:30 pm ET for their monthly webinar series, Data Science in 30 Minutes. Gregory will discuss his career, from AI to Data Mining to KDD to Data Science and back to AI, and examine current trends in the field.
- Everything Changes: A Human Perspective on Digitization - Jan 2, 2018.
An insightful, thought-provoking article on digital disruption and evolution of technology.
- Data Science in 30 Minutes: A Conversation with Gregory Piatetsky-Shapiro, President of KDnuggets, Jan 11 - Dec 14, 2017.
KDnuggets founder, Gregory Piatetsky-Shapiro, joins Michael Li, CEO and founder of The Data Incubator, Jan 11 at 2:30 pm PT/ 5:30 pm ET for their monthly webinar series, Data Science in 30 Minutes. Gregory will discuss his career - from Data Mining to Data Science and examine current trends in the field.
- Data Science, Machine Learning: Main Developments in 2017 and Key Trends in 2018 - Dec 12, 2017.
The leading experts in the field on the main Data Science, Machine Learning, Predictive Analytics developments in 2017 and key trends in 2018.
- KDnuggets™ News 17:n46, Dec 6: Why You Should Forget for-loop for Data Science Code; Reinforcement Learning: Exclusive Interview with Rich Sutton; Big Data Key Trends - Dec 6, 2017.
Also Big Data: Main Developments in 2017 and Key Trends in 2018; Exclusive: My interview with Rich Sutton, the Father of Reinforcement Learning; Understanding Deep Convolutional Neural Networks with a practical use-case in Tensorflow and Keras.
- Big Data: Main Developments in 2017 and Key Trends in 2018 - Dec 5, 2017.
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.
- When Will Demand for Data Scientists/Machine Learning Experts Peak? - Nov 7, 2017.
We analyze the results of Data Science / Machine Learning peak demand poll, examine the split between optimists and pessimists, and try to explain why predictions look so similar regardless of experience, affiliation, and region?
- 2 Machine Learning-related domain names for sale: Trendr.com and Predictive.ly - Oct 31, 2017.
Trendr.com is a great brand for companies performing any data analysis on trends. Predictive.ly is a perfect brand for a predictive analytics, machine learning, or data science company.
- New Poll: When will demand for Data Scientists/Machine Learning experts begin to decline? - Oct 23, 2017.
New KDnuggets Poll examines how long the current high demand for Data Scientists/Machine Learning experts will last. Please vote and we will analyze and report the results.
- 4 Major Trends Influencing the 2017 Predictive Analytics Hiring Market - Oct 17, 2017.
We examine the implications of trends in hiring market, including the growth of quantitative Initiatives, blurring of the lines between Predictive Analytics and Data Science Professionals, and more .
- Top 10 Active Big Data, Data Science, Machine Learning Influencers on LinkedIn, Updated - Sep 26, 2017.
Looking for advice? Guidance? Stories? We’ve put a list of the top ten LinkedIn influencers of the last three months, follow them and stay up-to-date with the latest news in Big Data, Data Science, Analytics, Machine Learning and AI.
- Deep Learning is not the AI future - Aug 25, 2017.
While Deep Learning had many impressive successes, it is only a small part of Machine Learning, which is a small part of AI. We argue that future AI should explore other ways beyond DL.
Pages: 1 2
- The Role of the Data Analyst in a Predictive Era - Aug 17, 2017.
Read "Analyst of the Future" guidebook to discover 3 emerging analyst roles and what they encompass, 4 trends transforming the world of data, and more.
- Intelligence and Cognition: I Do Not Think They Mean What You Think They Mean - Jul 21, 2017.
You have likely noticed the recent relative uptick in the use of the words "intelligence" and "cognitive," as well as their derivatives. Are such terms really true or are they a marketing device?
- KDnuggets™ News 17:n25, Jun 28: Emerging Data Science Software Ecosystem; 3 Key Data Science 2017 Hiring Trends - Jun 28, 2017.
Emerging Data Science Software Ecosystem; 3 Key Trends Shaping the 2017 Data Science Hiring Market; Top 10 Quora Machine Learning Writers and Their Best Advice; The world's first protein database for Machine Learning and AI; Making Sense of Machine Learning
- Hadoop is Not Failing, it is the Future of Data - Apr 27, 2017.
The author disagrees with a previous KDnuggets post on “Why Hadoop is Failing” and argues that the Darwinian Open Source Ecosystem ensures Hadoop is a robust and mature technology platform .
- DataScience Launches Interactive Tool For Exploring Data Science Trends - Apr 14, 2017.
DataScience Trends, a new interactive tool from DataScience Inc., gives users the ability to explore and visualize data across 2.8 million open source repositories without writing code.
- Data Science Trends To Look Out For In 2017 - Dec 8, 2016.
Machine Learning is here to stay, with more firms following Google and Facebook in the race to attract the best machine learning experts and Data Scientists. We also see a merger of IoT and Data Science. Read on for more trends.
- Evolution of the Data Scientist Through the Decade: What’s Changed - Oct 20, 2016.
Evolution is the truth of mankind and it’s inevitable. We all are evolutionizing everyday biologically as well as technologically and so do our roles and responsibilities. Here is the summary of evolution of Data Scientist role and it’s hiring trends in industry throughout the decade.
Pages: 1 2
- Data Science of Reviews: ReviewMeta tool Automatically Detects Unnatural Reviews on Amazon - Aug 23, 2016.
ReviewMeta is a tool that analyzes millions of reviews and helps customers decide which ones to trust. As the dataset grows, so do the insights on unbiased reviews.
- How to Use Cohort Data to Analyze User Behavior - Mar 10, 2016.
In the world of data analysis, cohorts are often pushed aside due to their seemingly complex nature. Learn what this analysis can offer and how to do it.
- Fastest Growing Programming Languages and Computing Frameworks - Mar 7, 2016.
A new model for ranking programming languages and predicting the growth of user adoption. Includes current language rankings and predictions.
- Businesses Will Need One Million Data Scientists by 2018 - Jan 28, 2016.
Deepening shortage of Data Science talent and cybersecurity challenges are trends shaping business in 2016.
- KDnuggets™ News 16:n02, Jan 20: Research Leaders on Key Advances, Top Trends; Top 10 Deep Learning Projects - Jan 20, 2016.
Research Leaders on Data Mining, Data Science and Big Data key advances, top trends; Top 10 Deep Learning Projects on Github; Top 100 Big Data Experts to Follow; Yahoo Releases the Largest-ever Machine Learning Dataset.
- Research Leaders on Data Mining, Data Science and Big Data key advances, top trends - Jan 18, 2016.
Research Leaders in Data Science and Big Data reflect on the most important research advances in 2015 and the key trends expected to dominate throughout 2016.
Pages: 1 2
- KDnuggets™ News 15:n42, Dec 29: Where did you apply Analytics? 5 ways Data Scientists keep learning - Dec 29, 2015.
Poll: Industries/Fields where you applied Analytics, Data Mining, Data Science in 2015; 5 Ways Data Scientists Keep Learning After College; Lessons from 2M Machine Learning Models on Kaggle; 10 BI Trends for 2016.
- 10 Business Intelligence Trends for 2016 - Dec 19, 2015.
BI analysts, industry players predict the rise of self-service, Big Data analytics, real-time data in the coming year.
Pages: 1 2
- Strata + Hadoop World 2015 Singapore – Day 1 Highlights - Dec 11, 2015.
Here are the quick takeaways and valuable insights from selected talks at one of the most reputed conferences in Big Data – Strata + Hadoop World 2015, Singapore.
- 22 Big Data & Data Science experts predictions for 2016 - Dec 11, 2015.
Will machines become smarter than man? What technology will dominate Data Science? What is smart data? Read Big Data experts predictions for 2016.
Pages: 1 2
- Salaries by Roles in Data Science and Business Intelligence - Sep 9, 2015.
Data Scientist is the hottest role. What's next? We present national average salaries, job title progression in career, job trends and skills for popular job titles in Data Science & Business Intelligence. Check out the salaries of related roles.
- Interview: Andrew Duguay, Prevedere on the Hidden Value in Global Data Sets - Jul 31, 2015.
We discuss the challenges in analyzing global economic datasets, impact of Big Data growth on economics, desired skills in data scientists, and more.
- Interview: Ramkumar Ravichandran, Visa on Customer-focus Mindset for Analytics - Jul 15, 2015.
We discuss career advice, need for customer-focus, Analytics trends, desired skills in Data Science practitioners, and more.
- Interview: Reiner Kappenberger, HP Security Voltage on Security Checklist for Data Architectures - Jul 10, 2015.
We discuss securing data-at-rest and data-in-motion, security recommendations for data architectures, trends, advice, and more.
- Interview: Anil Gadre, MapR on 3 Keys for Big Data Success: Reliability, Security, & Scalability - Jun 24, 2015.
We discuss the origin of Apache Myriad, state of security in Big Data, MapR Quick Start Solutions, Hadoop vendor selection criteria, and more.
- Interview: Joseph Babcock, Netflix on Curiosity and Courage – Key for Success in Data Science - Jun 17, 2015.
We discuss discovery vs. personalization, advice, trends, desired skills in data scientists, and more.
- Interview: Ranjan Sinha, eBay on Winner Insights from International Sorting Competitions - Jun 10, 2015.
We discuss advancements in the field of Personalization, lessons from winning sorting competitions, Data Science trends, career advice, and more.
- Interview: Antonio Magnaghi, TicketMaster on Why Honesty is Key for Analytics Success - May 19, 2015.
We discuss lessons from implementing lambda architecture, impact of Big Data on recommender systems, trends, advice, and more.
- Interview: Hobson Lane, SHARP Labs on How Analytics can Show You “All the Light You Cannot See” - May 14, 2015.
We discuss the impact of rapid growth in magnitude of data, programming skills for data science, major trends, advice, data science skills, and more.
- Interview: Mark Weiner, Temple University Health System on Addressing Healthcare Data Gaps through Advanced Simulation - May 12, 2015.
We discuss dealing with current gaps in healthcare data, challenges in using real world healthcare data, desired skills for data scientists in healthcare industry, advice, and more.
- Interview: Haile Owusu, Mashable on Surviving Imprecision in Digital Media Analytics - May 1, 2015.
We discuss the challenges in tracking social media sharing, advice, important trends, and more.
- Interview: Mario Vinasco, Facebook on Advancing Marketing Analytics through Rigorous Experimentation - Apr 27, 2015.
We discuss marketing analytics at Facebook, multi-channel performance assessment, success factors, lessons from Look Back feature, advice, and more.
Pages: 1 2
- Interview: Emmanuel Letouzé, Data-Pop Alliance on Big Data for Development and Future Prospects - Apr 25, 2015.
We discuss the field of Big Data for Development, current projects and future plans for Data-Pop Alliance, public participation opportunities, advice, and more.
Pages: 1 2
- Interview: Michael Li, Data Incubator on Bridging the Data Science Skills Gap between Academia and Industry - Apr 21, 2015.
We discuss the response from hiring companies, recommendations for aspirants, retaining data science talent, advice, and more.
- Interview: Ksenija Draskovic, Verizon on How to Not Get Lost in the Big Data Wilderness - Apr 16, 2015.
We discuss recommendations for data-driven decision making, challenges and benefits of using unstructured data, managing expectations and key trends.
- Interview: Michael Lurye, Time Warner Cable on Key Lessons from Shifting to Hadoop - Apr 14, 2015.
We discuss the key lessons from shifting to Hadoop, data management in today’s world, future of Data Science, advice and more.
- Interview: Alessandro Gagliardi, Glassdoor on the Fun and Boring Part of Data Scientist Job - Apr 3, 2015.
We discuss interesting trends, motivation, different aspects of data scientist job, advice, and more.
Pages: 1 2
- Interview: Satyam Priyadarshy, Halliburton on Unlocking Success for Big Data Projects - Mar 31, 2015.
We discuss Predictive Analytics in Oil & Gas industry, Big Data analytics, key drivers of success,common reasons of failure, trends, advice, and more.
- Interview: Bill Moreau, USOC on Evidence-based Medicine to Reduce Sports Injuries - Mar 27, 2015.
We discuss the success of Analytics in predicting sports injuries, recent progress in concussion management and the trends in data-driven evidence-based sports medicine.
- Interview: Beena Ammanath, GE on Data Science – It’s Not Just Science! - Mar 24, 2015.
We discuss benefits and challenges of Data Lake, trends, life lessons, motivation, desired skills, and more.
- Interview: Brad Klingenberg, StitchFix on Decoding Fashion through Analytics and ML - Mar 21, 2015.
We discuss the challenges in making personal styling recommendations, unexpected insights, interesting trends, motivation, advice, desired qualities in data scientists and more.
- Interview: Vince Darley, King.com on What do you need to become Top Grossing Game - Mar 19, 2015.
We discuss common characteristics of games that achieved top ranking, career advice, trends, desired qualities in data scientists and more.
- Interview: Kenneth Viciana, Equifax on Data Governance – Red Tape or Catalyst? - Mar 14, 2015.
We discuss recommendations for Data Governance policies, advice, Big Data trends, qualities sought in Data Scientists, and more.
- Interview: Slava Akmaev, Berg on Challenges in Transitioning Analytics to Clinical Utility - Mar 10, 2015.
We discuss Analytics use cases, challenges in relating molecular/clinical data to real-life outcomes, Healthcare Analytics trends and more.
- Interview: Lei Shi, ChinaHR.com on Unraveling Insights from Unstructured Data - Mar 7, 2015.
We discuss challenges in leveraging Big Data, important attributes while profiling employers and job seekers, competitive landscape, desired skills in data scientists and more.
- Interview: David Kasik, Boeing on Data Analysis vs Data Analytics - Feb 23, 2015.
We discuss the impact of increasing amount of data on visualization, difference between Data Analysis and Data Analytics, motivation, trends, desired skills and more.
- Interview: M.C. Srivas, CTO, MapR on Data Agility – The Next Frontier of Big Data - Feb 12, 2015.
We discuss the competitive differentiation of MapR, challenges in consumerizing Big Data, trends, strategy recommendations, desired skills and more.
- Top stories in January: (Deep Learning Deep Flaws) Deep Flaws; Research Leaders on key trends, papers - Feb 6, 2015.
Research Leaders on Data Science and Big Data key trends, papers; (Deep Learning Deep Flaws) Deep Flaws; Analytics: Five Rules to Cut Through the Hype; 11 Clever Methods of Overfitting and how to avoid them.
- Two Most Important Trends in Analytics and Big Data in 2015 - Feb 6, 2015.
In 2015, two most important trends in Analytics and Big Data are in developing countries and big data security.
- Interview: Rachel Hawley, SAS on Why Data Science Needs Communication Skills - Feb 4, 2015.
We discuss SAS Analytics Center of Excellence, trends, advice, desired skills in data science and more.
- Interview: Eli Collins, Cloudera on Evolution and Future of Big Data Ecosystem - Feb 2, 2015.
We discuss the change in Big Data priorities, risks, Big Data ecosystem, rise of data culture in organizations, challenges, advice and more.
- Interview: Anthony Bak, Ayasdi on Novel Insights using Topological Summaries - Jan 29, 2015.
We discuss examples of Topological Data Analysis (TDA) revealing new insights, recommended approach for creating Topological Summaries, Manual vs Automation approach and trends.
- Interview: Arno Candel, H20.ai on How to Quick Start Deep Learning with H2O - Jan 21, 2015.
We discuss H2O use cases, resources to start using H2O for Deep Learning, evolution of High Performance Computing (HPC) and the future of HPC.
- 8 Trends In Big Data For 2015 - Jan 21, 2015.
2015 trends include Non-Data Scientists, Real Time Big Data, Self Service Big Data, Shared Big Data, Big Data and IoT, Richer Data, More Big Data Geeks, and Creative Recruitment - read why.
- Top stories for Jan 11-17: Research Leaders on Data Mining/Big Data key trends, top papers; Deep Learning in a Nutshell - Jan 18, 2015.
Research Leaders on Data Mining, Data Science, and Big Data key trends, top papers; Deep Learning in a Nutshell - what it is, how it works, why care?; Deep Learning can be easily fooled; Cartoon: Hello, Singularity.
- KDnuggets™ News 15:n02, Jan 14: Research Leaders on key trends, top papers; Exclusive NYTimes interview - Jan 14, 2015.
Research Leaders on Data Mining key trends, top papers; Exclusive Interview with NYTimes Chief Data Scientist; Majority thinks AI not a threat; Cartoon: Hello, Singularity; Deep Learning in a Nutshell; How to make Privacy and Data Mining Compatible; ClearStory Data CEO on Collaborative Storyboards.
- Interview: Miriah Meyer, Univ. of Utah on the Art and Science of Visualization - Jan 12, 2015.
We discuss insights from the best paper at ACM AVI 2014, increasing interest in visualization, infographics, trends, challenges, advice and more.
- Top stories for Jan 4-10: 11 Clever Methods of Overfitting; Research Leaders on Data Science and Big Data - Jan 11, 2015.
11 Clever Methods of Overfitting and how to avoid them; Causation vs Correlation: Visualization, Statistics, and Intuition; Research Leaders on Data Science and Big Data key trends, top papers; Differential Privacy: How to make Privacy and Data Mining Compatible.
- Interview: Sharmila Mulligan, ClearStory Data on Variety & Velocity to be Big Data Priorities - Jan 10, 2015.
We discuss the ClearStory Data’s competitive differentiation, client use case, Big Data trends, advice, desired soft skills in data scientists and more.
- Interview: Ben Werther, CEO, Platfora on Insightful Analytics for Big Data - Dec 30, 2014.
We discuss the challenges in implementing end-to-end solutions for Big Data, Platfora use cases, Big Data trends, advice and more.
- Interview: Mac Devine, CTO, IBM Cloud on the Conflux of Cloud, IoT & Big Data - Dec 26, 2014.
We discuss the implications of Cloud Speed of technological advancement, significant trends in Internet of Things (IoT), future of cloud computing and more.
- Hot or Not: Data Science Trends in 2015 - Dec 24, 2014.
CrowdFlower infographic predicts the hot trends for data science in 2015 and which trends will fade away.
- Interview: Peter Alvaro, UC Berkeley, on Managing Asynchrony and Partial Failure - Dec 18, 2014.
We discuss the challenges in simultaneously managing asynchrony and partial failure, the problem of composition, research motivation, trends and more.
- KDnuggets Interview: Paul Zikopoulos, IBM on Big Data Opportunities and Challenges - Dec 14, 2014.
We discuss the value of Big Data for SMBs, how Cognitive will impact Big Data, IBM’s distinction from competition, significant trends and more.
- Top KDnuggets tweets, Nov 24-25: Why So Many Data Ideas Fail: beware of building on public or others data - Nov 28, 2014.
Why So Many Data Ideas Fail: beware of building on public or others data; #BigData Top Trends in 2015: In-memory DBs, Non-Data Scientists, Sensor Data ...; Hackathon pits data scientists against social problems; Great course: Intro to Statistical Learning, with Applications in R.
- Interview: Philip Maymin, NYU on Why Sports should Embrace Analytics? - Nov 22, 2014.
We discuss how the increasing use of Analytics will change the game of basketball, the concern of Analytics ruining the game, significant trends, advice and more.