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KDnuggets News: 2019 News | Schedule | Submissions | Archive
Top stories: Most viewed and Most shared
KDnuggets News: 2019 News | Schedule | Submissions | Archive
Latest:
Extracting Knowledge from Knowledge Graphs Using Facebook’s Pytorch-BigGraph - May 22, 2019.
We are building a model, which is trying to predict the word using the words it’s surrounded by as labels.
Murmuration: Data Engineer [New York, NY] - May 22, 2019.
Seeking an innovative Data Engineer to maintain and architect the data systems and pipelines to support our efforts. The Data Engineer would work with our Senior Data Engineer and use a variety of leading database technologies and tools to process and store our existing data.
6 Industries Warming up to Predictive Analytics and Forecasting - May 22, 2019.
Here are six sectors that are realizing how beneficial predictive analytics could be, embracing the possibilities of valuable insights extracted from such technology.- KDnuggets™ News 19:n20, May 22: 7 Steps to Mastering SQL for Data Science; How to build Math Programming Skills - May 22, 2019.
Also An overview of Pycharm for Data Scientists; How to build a Computer Vision model - key approaches and datasets; k-means clustering tutorial; 60+ useful graph visualization libraries; The Data Fabric for Machine Learning. - Apple: Software Engineer, Ad Platforms [Cupertino, CA] - May 21, 2019.
Seeking an engineer for the Core Services Platform team, which designs and builds best of breed systems for dealing with our complex and ever-growing data and infrastructure platform needs that help run campaigns and deliver advertising content deliver advertising data to Ad Server and Big Data pipelines. - Apple: Data Scientist, Ad Platforms [Cupertino, CA] - May 21, 2019.
Seeking a self-motivated individual that will build out the next generation of our ads platforms. Projects range from generating algorithms that drive our auctions to building out data products to help our advertisers manage the efficiency and quality of their campaign strategies. - How do you teach physics to machine learning models? - May 21, 2019.
How to integrate physics-based models (these are math-based methods that explain the world around us) into machine learning models to reduce its computational complexity. - Probability Mass and Density Functions - May 21, 2019.
This content is part of a series about the chapter 3 on probability from the Deep Learning Book by Goodfellow, I., Bengio, Y., and Courville, A. (2016). It aims to provide intuitions/drawings/python code on mathematical theories and is constructed as my understanding of these concepts. - The Data Fabric for Machine Learning – Part 1 - May 21, 2019.
How the new advances in semantics and the data fabric can help us be better at Machine Learning 
Customer Support Chatbots: Easier & More Effective Than You Think - May 20, 2019.
Learn how to create your own free chatbot environment with just a few commands, as well as learning more about the benefits of customer service chatbots.- 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. 
Top Stories, May 13-19: 7 Steps to Mastering SQL for Data Science — 2019 Edition; Mathematical programming — Key Habit to Build Up for Advancing Data Science - May 20, 2019.
Also: Machine Learning in Agriculture: Applications and Techniques; 60+ useful graph visualization libraries; How (not) to use Machine Learning for time series forecasting: Avoiding the pitfalls; The Third Wave Data Scientist; The 3 Biggest Mistakes on Learning Data Science- Autoencoders: Deep Learning with TensorFlow’s Eager Execution - May 20, 2019.
Deep Learning has revolutionized the Machine Learning scene in the last years. Can we apply it to image compression? How well can a Deep Learning algorithm reconstruct pictures of kittens? What’s an autoencoder? - Monash University: Research Fellow – Optimisation [Melbourne, Australia] - May 17, 2019.
Seeking an enthusiastic researcher with solid skills in any of the following areas: constraint programming, mixed integer programming, SAT and SAT modulo theories, modelling languages and program analysis, to join an established team working on new approaches to modelling and solving discrete optimisation problems. - 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. - 60+ useful graph visualization libraries - May 17, 2019.
We outline 60+ graph visualization libraries that allow users to build applications to display and interact with network representations of data. - PyCharm for Data Scientists - May 17, 2019.
This article is a discussion of some of PyCharm's features, and a comparison with Spyder, an another popular IDE for Python. Read on to find the benefits and drawbacks of PyCharm, and an outline of when to prefer it to Spyder and vice versa. -
7 Steps to Mastering SQL for Data Science — 2019 Edition - May 17, 2019.
Follow these updated 7 steps to go from SQL data science newbie to practitioner in a hurry. We consider only the necessary concepts and skills, and provide quality resources for each. - A complete guide to K-means clustering algorithm - May 16, 2019.
Clustering - including K-means clustering - is an unsupervised learning technique used for data classification. We provide several examples to help further explain how it works. - Why Data Professionals Should Negotiate Every Job Offer - May 16, 2019.
Here are six reasons why you shouldn't feel tempted to jump at the chance and take that job offer as it is without first negotiating. - Large-Scale Evolution of Image Classifiers - May 16, 2019.
Deep neural networks excel in many difficult tasks, given large amounts of training data and enough processing power. The neural network architecture is an important factor in achieving a highly accurate model... Techniques to automatically discover these neural network architectures are, therefore, very much desirable. - Top KDnuggets tweets, May 08-14: The end of average Data Scientist is near: @GoogleAI fully automated, End-to-End #AutoML #MachineLearning - May 15, 2019.
Also: My favorite free courses to learn data structures and #algorithms in depth; “Please, explain.” Interpretability of machine learning models; Decoding ‘A Game of Thrones’ #GOT with data science; Another 10 Free Must-See Courses for Machine Learning and Data Science; Best Data Visualization Techniques for small and large data - Building Recommender systems with Azure Machine Learning service - May 15, 2019.
Microsoft has provided a GitHub repository with Python best practice examples to facilitate the building and evaluation of recommendation systems using Azure Machine Learning services. - Mathematical programming — Key Habit to Build Up for Advancing Data Science - May 15, 2019.
We show how, by simulating the random throw of a dart, you can compute the value of pi approximately. This is a small step towards building the habit of mathematical programming, which should be a key skill in the repertoire of a budding data scientist. - Monash University: Lecturer / Senior Lecturer – Optimisation [Melbourne, Australia] - May 15, 2019.
Seeking outstanding academics to join our world-class team to deliver high-quality teaching and research that will help shape the future of optimisation for energy, transport, health and many other application domains. Positions are available for academics with strong skills in the development and application of techniques discrete optimisation research. - KDnuggets™ News 19:n19, May 15: Data Scientist – Best Job of the Year!; How (not) to use Machine Learning for time series forecasting - May 15, 2019.
"Please, explain." Interpretability of machine learning models; How to fix an Unbalanced Dataset; Data Science Poem; Customer Churn Prediction Using Machine Learning; A Complete Exploratory Data Analysis and Visualization for Text - Customer Churn Prediction Using Machine Learning: Main Approaches and Models - May 14, 2019.
We reach out to experts from HubSpot and ScienceSoft to discuss how SaaS companies handle the problem of customer churn prediction using Machine Learning. - Monash University: Lecturer / Sr Lecturer in IT for Energy [Melbourne, Australia] - May 14, 2019.
Seeking a Lecturer/Senior Lecturer for our IT for Energy theme. As Monash’s energy research front, Monash Energy Materials and Systems Institute (MEMSI) is focused on developing solutions to enable sustainable generation, storage, distribution, visualisation and end-use of energy. -
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. - Brookhaven National Laboratory: Postdoc in Materials Informatics [Upton, NY] - May 14, 2019.
Seeking candidates to develop and apply information retrieval, information extraction, and various Natural Language Processing (NLP) techniques to the scientific literature in materials science and crystallography for the purpose of building prototype computational data systems. - 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. - Top Stories, May 6-12: The Third Wave Data Scientist; The 3 Biggest Mistakes on Learning Data Science - May 13, 2019.
Also: Data Scientist Best Job of the Year in USA; How (not) to use Machine Learning for time series forecasting: Avoiding the pitfalls; 2019 KDnuggets Poll: What software you used for Analytics, Data Mining, Data Science, Machine Learning projects in the past 12 months?; The most desired skill in data science; Please, explain. Interpretability of machine learning 
From Prediction to Decision at Predictive Analytics World – London & Berlin - May 13, 2019.
Top expert practitioners will gather in London (16-17 Oct) and Berlin (18-19 Nov), at the premier vendor-neutral machine learning conference, to describe the design, deployment and business impact of their machine learning projects.- What my first Silver Medal taught me about Text Classification and Kaggle in general? - May 13, 2019.
A first-hand account of ideas tried by a competitor at the recent kaggle competition 'Quora Insincere questions classification', with a brief summary of some of the other winning solutions. - Modeling 101 - May 13, 2019.
In the past couple of decades, innovation in statistics and machine learning has been increasing at a rapid pace and we are now able to do things unimaginable when I began my career. - Data Science Poem - May 11, 2019.
A poem about Data Science. - Data Science in the Senses - May 10, 2019.
The evening event at the Rev conference this year will be showcasing some amazing projects that leverage data and machine learning for sensory experiences. - Intuit: Sr Manager Data and Analytics – Speech and Text Insights [Mountain View, CA] - May 10, 2019.
Seeking a Sr Manager Data and Analytics for Speech and Text Insights, to oversee the design, development, deployment and management of batch and real-time fraud and credit risk models for both onboarding and monitoring purposes. - How (not) to use Machine Learning for time series forecasting: Avoiding the pitfalls - May 10, 2019.
We outline some of the common pitfalls of machine learning for time series forecasting, with a look at time delayed predictions, autocorrelations, stationarity, accuracy metrics, and more. - Intuit: Business Operations Analyst [Mountain View, CA] - May 10, 2019.
Seeking a Business Operations Analyst, a creative problem solver with a passion for innovation, technology and teams to help us revolutionize the way small businesses run their business and deliver on our mission of “powering prosperity around the world.” - Intuit: Group Manager, Accountant Segment Data Science and Analytics [Mountain View, CA] - May 10, 2019.
Seeking creative problem solvers with a passion to deliver data-driven insights. This position leads a team of talented analysts and scientists to work alongside with business stakeholders to deliver customer insights and recommendations. - Intuit: Sr Data Scientist – Business Analytics [Mountain View, CA] - May 10, 2019.
Seeking a great data scientist for our Quickbooks Online (QBO) business. You need to be a top-notch problem solver and problem identifier as there are no points for an elegant solution to the wrong problem. It’s also a good idea to know the standard suite of analytical tools but more importantly you must know how to learn tools quickly. - Intuit: Sr Data Scientist, Business Analytics [Mountain View, CA] - May 10, 2019.
Seeking a hands-on Senior Data Scientist in the Data Analytics & Science team, someone who is a creative problem solver with a passion to deliver advanced data-driven solutions. - 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. - 5 Things to Review Before Accepting That Data Scientist Job Offer - May 10, 2019.
Before you get too excited and sign the papers for that new data scientist job, and solidify your role as a new hire, make sure you look over these 5 things first. - Top April Stories: The most desired skill in data science; Top 10 Coding Mistakes Made by Data Scientists - May 10, 2019.
Also: Another 10 Free Must-See Courses for Machine Learning and Data Science; How to Recognize a Good Data Scientist Job From a Bad One. - 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. - Books on Graph-Powered Machine Learning, Graph Databases, Deep Learning for Search – 50% off - May 9, 2019.
These 3 books will help you make the most from graph-powered databases. For a limited time, get 50% off any of them with the code kdngraph. - “Please, explain.” Interpretability of machine learning models - May 9, 2019.
Unveiling secrets of black box models is no longer a novelty but a new business requirement and we explain why using several different use cases. - A Complete Exploratory Data Analysis and Visualization for Text Data: Combine Visualization and NLP to Generate Insights - May 9, 2019.
Visually representing the content of a text document is one of the most important tasks in the field of text mining as a Data Scientist or NLP specialist. However, there are some gaps between visualizing unstructured (text) data and structured data. - Intuit: Sr Data Scientist, Technical Analytics [Mountain View, CA] - May 9, 2019.
Come join Intuit as a Senior Technical Data Analyst, and partner closely with business and technical teams to understand their project objectives and provide data-driven solutions and recommendations. - Intuit: Sr Data Scientist, Business Analytics [Mountain View, CA] - May 9, 2019.
Seeking creative problem solvers with a passion to deliver data-driven insights. This position works alongside product manager, product developer, and analytics partners to deliver business results using data for insights and optimization. - Intuit: Group Manager Data Science and Analytics [Mountain View, CA] - May 9, 2019.
Seeking an analytics leader to build out our team and provide analytical leadership for the business, and to lead and develop a team while also rolling up their sleeves and get work done when that is what’s needed. - Intuit: Staff Data Scientist, Experimentation Analytics [Mountain View, CA] - May 9, 2019.
Intuit is seeking a Staff Data Scientist to join our team, to help build a new business within the company in one of the hottest fintech spaces of the moment. - Intuit: Experimentation Leader, Data Science and Analytics [Mountain View, CA] - May 9, 2019.
Seeking a Principal Experimentation Data Scientist, a creative problem solver with a passion for delivering data-driven insights, a deep knowledge of Testing and Experimentation to optimize digital experiences. - Top KDnuggets tweets, May 01-07: The 3 Biggest Mistakes in Learning Data Science; ReinforcementLearning vs. Differentiable Programming; XGBoost Reign - May 8, 2019.
Also XGBoost Algorithm: Long May She Reign; CycleGANs to Create Computer-Generated #Art - #GANs #DeepLearning; Another 10 Free Must-See Courses for Machine Learning and Data Science. - Data Scientist – Best Job of the Year in USA - May 8, 2019.
CareerCast ranks Data Scientist as the top job in USA, with very good work environment, low stress, high growth, and median salary of $114,520. - [White Paper] Unlocking the Power of Data Science & Machine Learning with Python - May 8, 2019.
This guide from ActiveState provides an executive overview of how you can implement Python for your team’s data science and machine learning initiatives. - How to fix an Unbalanced Dataset - May 8, 2019.
We explain several alternative ways to handle imbalanced datasets, including different resampling and ensembling methods with code examples. - Linear Programming and Discrete Optimization with Python using PuLP - May 8, 2019.
Knowledge of such optimization techniques is extremely useful for data scientists and machine learning (ML) practitioners as discrete and continuous optimization lie at the heart of modern ML and AI systems as well as data-driven business analytics processes. - Intro to XGBoost: Predicting Life Expectancy with Supervised Learning - May 8, 2019.
Today we’ll use XGBoost Boosted Trees for regression over the official Human Development Index dataset. XGBoost is a framework that allows us to train Boosted Trees exploiting multicore parallelism. - KDnuggets™ News 19:n18, May 8: What Data Science/Machine Learning software you used – KDnuggets Poll; The Third Wave Data Scientist - May 8, 2019.
Vote in KDnuggets 20th annual poll: What software you used for Analytics, Data Mining, Data Science, Machine Learning projects? Also, what skills are needed for the 3rd wave Data Scientist?; The 3 biggest mistakes in learning Data Science; What makes XGBoost so successful; The ranking of best Masters in Analytics/Data Science in US/Canada; and more. - 2019 KDnuggets Poll: What software you used for Analytics, Data Mining, Data Science, Machine Learning projects in the past 12 months? - May 7, 2019.
Vote in KDnuggets 20th Annual Poll: What software you used for Analytics, Data Mining, Data Science, Machine Learning projects in the past 12 months? We will publish the anon data, results, and trends here. 
Building an Effective Data Science Project Portfolio: A Live Webinar by Metis | May 15 | 1pm ET - May 7, 2019.
This workshop is designed for business leaders, data science managers, and decision makers who want to ensure the effectiveness of the AI and data science capabilities they are building.- Best US/Canada Masters in Analytics, Business Analytics, Data Science - May 7, 2019.
In the final part of this series, we provide an updated list of our comprehensive, unbiased survey of graduate programs in Data Science and Analytics from across the US and Canada. - Naive Bayes: A Baseline Model for Machine Learning Classification Performance - May 7, 2019.
We can use Pandas to conduct Bayes Theorem and Scikitlearn to implement the Naive Bayes Algorithm. We take a step by step approach to understand Bayes and implementing the different options in Scikitlearn. - Data Science vs. Decision Science - May 7, 2019.
Data science and decision science are related but still separate fields, so at some points, it might be hard to compare them directly. We attempted to show our vision of the commonalities, differences, and specific features of data science and decision science. - Top Stories, Apr 29 – May 5: The most desired skill in data science; Top Data Science and Machine Learning Methods Used in 2018, 2019 - May 6, 2019.
Also: Normalization vs Standardization — Quantitative analysis; Build Your First Chatbot Using Python & NLTK; Which Deep Learning Framework is Growing Fastest?; Pandas DataFrame Indexing; XGBoost Algorithm: Long May She Reign - Virginia Tech: Data Engineer [Blacksburg, VA] - May 6, 2019.
The Office of Academic Decision Support is looking for a data engineer to help design and build data pipelines and data systems to support the development of data products and solutions that will help decision makers at all levels of the institution gain insights. - Virginia Tech: Full Stack Web Application Developer [Blacksburg, VA] - May 6, 2019.
The Office of Academic Decision Support is looking for a talented Full stack web application developer to build high performance web based analytical applications with intuitive interfaces and visual insights. 
Business analytics programs online - May 6, 2019.
Penn State's 9-credit Graduate Certificate in Business Analytics can help you learn to perform analytics tasks in critical business areas. Apply now.- Unleash Big Data by SaaS-based End-to-End AutoML - May 6, 2019.
This SaaS-based end-to-end AutoML tool R2 Learn enables data scientists, developers and data analysts to increase productivity, reduce errors and build quality models. Try for Free today! - The Third Wave Data Scientist - May 6, 2019.
An extensive look at what skills are needed to make up the portfolio of the third wave of data scientists. - The 3 Biggest Mistakes on Learning Data Science - May 6, 2019.
Data science or whatever you want to call it is not just knowing some programming languages, math, statistics and have “domain knowledge” and here I show you why. - Statistical Thinking for Industrial Problem Solving (STIPS) – a free online course. - May 3, 2019.
This online course is available – for free – to anyone interested in building practical skills in using data to solve problems better. - 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. - How to Automate Tasks on GitHub With Machine Learning for Fun and Profit - May 3, 2019.
Check this tutorial on how to build a GitHub App that predicts and applies issue labels using Tensorflow and public datasets. - XGBoost Algorithm: Long May She Reign - May 2, 2019.
In recent years, XGBoost algorithm has gained enormous popularity in academic as well as business world. We outline some of the reasons behind this incredible success. - Modeling Price with Regularized Linear Model & XGBoost - May 2, 2019.
We are going to implement regularization techniques for linear regression of house pricing data. Our goal in price modeling is to model the pattern and ignore the noise. - Top KDnuggets tweets, Apr 24–30: Another 10 Free Must-Read Books for Machine Learning and Data Science; Top #DataScience & #MachineLearning Methods Used in 2018/19 - May 1, 2019.
Also: Data Visualization in Python: Matplotlib vs Seaborn; Data Science Project Flow for Startups; Pandas DataFrame Indexing; Best Data Visualization Techniques for small and large data; The most desired skill in #DataScience - How to correctly select a sample from a huge dataset in machine learning - May 1, 2019.
We explain how choosing a small, representative dataset from a large population can improve model training reliability. - Which Deep Learning Framework is Growing Fastest? - May 1, 2019.
In September 2018, I compared all the major deep learning frameworks in terms of demand, usage, and popularity. TensorFlow was the champion of deep learning frameworks and PyTorch was the youngest framework. How has the landscape changed? - Build Your First Chatbot Using Python & NLTK - May 1, 2019.
Today we will learn to create a simple chat assistant or chatbot using Python’s NLTK library. - KDnuggets™ News 19:n17, May 1: The most desired skill in data science; Seeking KDnuggets Editors, work remotely - May 1, 2019.
This week, find out about the most desired skill in data science, learn which projects to include in your portfolio, identify a single strategy for pulling data from a Pandas DataFrame (once and for all), read the results of our Top Data Science and Machine Learning Methods poll, and much more. - Powerful like your local notebook. Sharable like a Google Doc. - Apr 30, 2019.
Mode is the only analytics platform with native Python and R Notebooks. Get everyone up and running in minutes by delivering Notebook-powered results right in your browser. Now anyone on your team can re-run R- and Python-powered reports themselves—without ever touching code. - Top Stories, Apr 22-28: The most desired skill in data science; How To Go Into Data Science: Ultimate Q&A for Aspiring Data Scientists - Apr 30, 2019.
Artificial Intelligence 101 Cheatsheet; AI Supporting The Earth; Data Visualization in Python: Matplotlib vs Seaborn; 2019 Best Masters in Data Science and Analytics Online; Graduating in GANs: Going From Understanding Generative Adversarial Networks to Running Your Own - Learn About Data Science & the Future of Investing from Hedge Fund Leaders at Rev 2 - Apr 30, 2019.
Rev 2 features interactive sessions, Q&A with industry luminaries, poster sessions for interesting modeling techniques and accomplishments, and stimulating conversations about how to make data science an enterprise-grade capability. - Interview Questions for Data Science – Three Case Interview Examples - Apr 30, 2019.
Part two in this series of useful posts for aspiring data scientists focuses on case interviews and how you can best go about answering them. - Seeking KDnuggets Editors, part-time, work remotely - Apr 30, 2019.
Help publish a leading blog on AI, Data Science, and Machine Learning! Looking for KDnuggets Editors, part-time, preferably able to work in US/Canada timezones. All work is done remotely and compensation is quite competitive. -
Normalization vs Standardization — Quantitative analysis - Apr 30, 2019.
Stop using StandardScaler from Sklearn as a default feature scaling method can get you a boost of 7% in accuracy, even when you hyperparameters are tuned!