Data Science (1148)

• Data Observability: Building Data Quality Monitors Using SQL - Feb 16, 2021.
  
  To trigger an alert when data breaks, data teams can leverage a tried and true tactic from our friends in software engineering: monitoring and observability. In this article, we walk through how you can create your own data quality monitors for freshness and distribution from scratch using SQL.

  Data Engineering, Data Quality, Data Science, Data Science Platform, SQL

• Essential Math for Data Science: Scalars and Vectors - Feb 12, 2021.
  
  Linear algebra is the branch of mathematics that studies vector spaces. You’ll see how vectors constitute vector spaces and how linear algebra applies linear transformations to these spaces. You’ll also learn the powerful relationship between sets of linear equations and vector equations.

  Data Science, Linear Algebra, Mathematics

• Online MS in Data Science from Northwestern - Feb 11, 2021.
  
  Advance your data science career with Northwestern. Build the essential technical, analytical, and leadership skills needed for careers in today's data-driven world in Northwestern's Master of Science in Data Science program. Apply now.

  Data Science, MS in Data Science, Northwestern, Online Education

• Data Science vs Business Intelligence, Explained - Feb 10, 2021.
  
  Knowing the differences between the business intelligence and data science is more than just a matter of semantics.

  BI, Business Intelligence, Data Science, Explained

• Who is fit to lead data science? - Feb 9, 2021.
  
  Data science success depends on leaders, not the latest hands-on programming skills. So, we need to start looking for the right leadership skills and stop stuffing job postings with requirements for experience in the most current development tools.

  Business, Career Advice, Data Leadership, Data Science, Data Scientist, TensorFlow

• How to Get Data Science Interviews: Finding Jobs, Reaching Gatekeepers, and Getting Referrals - Feb 8, 2021.
  
  In this post, the author shares what to do to get job interviews efficiently. Find answers to these questions: Where should I look for data science jobs? How do I reach out to the gatekeeper? How do I get referrals? What makes a good data science resume?

  Career Advice, Careers, Data Science, Jobs

• The Best Data Science Project to Have in Your Portfolio - Feb 8, 2021.
  
  If you are trying to find your first path into a Data Science career, then demonstrating the quality of your skills can be the greatest hurdle. While many standard projects exist for anyone to complete, creating an original data-driven project that attempts to solve some challenge is worth so much more. A good Data Scientist is one that can solve data-related questions, and a great Data Scientist poses original data-related questions and then solves.

  Career Advice, Data Science, Portfolio

• Essential Math for Data Science: Introduction to Matrices and the Matrix Product - Feb 5, 2021.
  
  As vectors, matrices are data structures allowing you to organize numbers. They are square or rectangular arrays containing values organized in two dimensions: as rows and columns. You can think of them as a spreadsheet. Learn more here.

  Data Science, Linear Algebra, Mathematics, numpy, Python

• Build Your First Data Science Application - Feb 4, 2021.
  
  Check out these seven Python libraries to make your first data science MVP application.

  API, Data Science, Jupyter, Keras, numpy, Pandas, Plotly, Python, PyTorch, scikit-learn

• One question to make your data project 10x more valuable - Feb 1, 2021.
  
  If you are the "data person" for your organization, then providing meaningful results to stakeholder data requests can sometimes feel like shots in the dark. However, you can make sure your data analysis is actionable by asking one magic question before getting started.

  Advice, Business, Data Analysis, Data Mining, Data Science, Deployment, Problem Definition

• Top 5 Reasons Why Machine Learning Projects Fail - Jan 28, 2021.
  
  The rise in machine learning project implementation is coming, as is the the number of failures, due to several implementation and maintenance challenges. The first step of closing this gap lies in understanding the reasons for the failure.

  Data Preparation, Data Science, Failure, Implementation, Machine Learning

• How to Get a Job as a Data Scientist - Jan 27, 2021.
  
  Here’s a step-by-step guide to starting your career in data science.

  Career Advice, Data Science, Data Scientist

• Cloud Computing, Data Science and ML Trends in 2020–2022: The battle of giants - Jan 22, 2021.
  
  Kaggle’s survey of ‘State of Data Science and Machine Learning 2020’ covers a lot of diverse topics. In this post, we are going to look at the popularity of cloud computing platforms and products among the data science and ML professionals participated in the survey.

  AWS, Cloud Computing, Data Science, Google Cloud, Kaggle, Machine Learning, Microsoft Azure, Trends

• Graph Representation Learning: The Free eBook - Jan 19, 2021.
  
  This free eBook can show you what you need to know to leverage graph representation in data science, machine learning, and neural network models.

  Data Science, Free ebook, Graph, Neural Networks, Representation

• Build a Data Science Portfolio that Stands Out Using These Platforms - Jan 19, 2021.
  
  Making your big break into the data science profession means standing out to potential employers in a crowd of tough competition. An important way to showcase your skills and experience is through the presentation of a portfolio. Following these recommendations for developing your portfolio will help you network effectively and stay on top of an ever-changing field.

  Career Advice, Data Science, GitHub, Kaggle, LinkedIn, Portfolio

• Can Data Science Be Agile? Implementing Best Agile Practices to Your Data Science Process - Jan 18, 2021.
  
  Agile is not reserved for software developers only -- that's a myth. While these effective strategies are not commonly used by data scientists today and some aspects of data science make Agile a bit tricky, the methodology offers plenty of benefits to data science projects that can increase the effectiveness of your process and bring more success to your outcomes.

  Agile, Best Practices, Data Science, Development

• Essential Math for Data Science: Information Theory - Jan 15, 2021.
  
  In the context of machine learning, some of the concepts of information theory are used to characterize or compare probability distributions. Read up on the underlying math to gain a solid understanding of relevant aspects of information theory.

  Data Science, Mathematics

• 8 New Tools I Learned as a Data Scientist in 2020 - Jan 14, 2021.
  
  The author shares the data science tools learned while making the move from Docker to Live Deployments.

  Data Science, Data Science Tools, Data Scientist, Deployment, Docker, Kubernetes, MLflow, NoSQL

• My Data Science Learning Journey So Far - Jan 13, 2021.
  
  These are some obstacles the author faced in their data science learning journey in the past year, including how much time it took to overcome each obstacle and what it has taught the author.

  Career Advice, Challenges, Data Science, Data Science Education

• The Four Jobs of the Data Scientist - Jan 13, 2021.
  
  So, what do you do for a living? Sometimes, the answer to that question can feel like, "everything!" Well, for the Data Scientist, an extreme sense of being a "jack of all trades" is common. In fact, four such trades can be defined that a top-quality Data Scientist will iterate through during any one project.

  Data Science, Data Science Skills, Data Scientist, Statistician

• 5 Tools for Effortless Data Science - Jan 11, 2021.
  
  The sixth tool is coffee.

  Data Science, Data Science Tools, Keras, Machine Learning, MLflow, PyCaret, Python

• JupyterLab 3 is Here: Key reasons to upgrade now - Jan 8, 2021.
  
  Read about these 3 reasons for checking out JupyterLab 3 today.

  Data Science, IDE, Jupyter, Programming

• MLOps: Model Monitoring 101 - Jan 6, 2021.
  
  Model monitoring using a model metric stack is essential to put a feedback loop from a deployed ML model back to the model building stage so that ML models can constantly improve themselves under different scenarios.

  AI, Data Science, DevOps, Machine Learning, MLOps, Modeling

• Where is Marketing Data Science Headed? - Jan 5, 2021.
  
  Marketing data science - data science related to marketing - is now a significant part of marketing. Some of it directly competes with traditional marketing research and many marketing researchers may wonder what the future holds in store for it.

  Analytics, Data Science, Marketing

• Model Experiments, Tracking and Registration using MLflow on Databricks - Jan 5, 2021.
  
  This post covers how StreamSets can help expedite operations at some of the most crucial stages of Machine Learning Lifecycle and MLOps, and demonstrates integration with Databricks and MLflow.

  Data Science, Databricks, DataOps, Experimentation, MLflow, MLOps, Modeling, StreamSets

• Six Tips on Building a Data Science Team at a Small Company - Jan 4, 2021.
  
  When a company decides that they want to start leveraging their data for the first time, it can be a daunting task. Many businesses aren’t fully aware of all that goes into building a data science department. If you're the data scientist hired to make this happen, we have some tips to help you face the task head-on.

  Data Science, Data Science Team, Data Scientist

• 15 Free Data Science, Machine Learning & Statistics eBooks for 2021 - Dec 31, 2020.
  
  We present a curated list of 15 free eBooks compiled in a single location to close out the year.

  Automated Machine Learning, Data Science, Deep Learning, Free ebook, Machine Learning, NLP, Python, R, Statistics

• Data Science as a Product – Why Is It So Hard? - Dec 30, 2020.
  
  Developing machine learning models as products that deliver business value remains a new field with uncharted paths toward success. Applying well-established software development approaches, such as agile, is not straightforward, but may still offer a solid foundation to guide success.

  Agile, Data Science, Deployment, Product

• Essential Math for Data Science: The Poisson Distribution - Dec 29, 2020.
  
  The Poisson distribution, named after the French mathematician Denis Simon Poisson, is a discrete distribution function describing the probability that an event will occur a certain number of times in a fixed time (or space) interval.

  Data Science, Distribution, Mathematics, Poisson Distribution

• Data Catalogs Are Dead; Long Live Data Discovery - Dec 28, 2020.
  
  Why data catalogs aren’t meeting the needs of the modern data stack, and how a new approach – data discovery – is needed to better facilitate metadata management and data reliability.

  Data Catalog, Data Discovery, Data Science, Data Science Platform

• MLOps – “Why is it required?” and “What it is”? - Dec 18, 2020.
  
  Creating an model that works well is only a small aspect of delivering real machine learning solutions. Learn about the motivation behind MLOps, the framework and its components that will help you get your ML model into production, and its relation to DevOps from the world of traditional software development.

  Data Science, DevOps, MLOps

• 8 Places for Data Professionals to Find Datasets - Dec 17, 2020.
  
  Here is a curated list of sites and resources invaluable for data professionals to acquire practice datasets.

  Data Science, Datasets, Google, Government, Kaggle, Reddit, UCI

• Applications of Data Science and Business Analytics - Dec 15, 2020.
  
  In recent times, a large number of businesses have begun realising the potential of Data Science. Business analytics and data science applications are far and wide. So let us have a look at them in detail.

  Applications, Business, Data Science, Genomics, Great Learning, Search, Virtual Assistant

• Data Science and Machine Learning: The Free eBook - Dec 15, 2020.
  
  Check out the newest addition to our free eBook collection, Data Science and Machine Learning: Mathematical and Statistical Methods, and start building your statistical learning foundation today.

  Data Science, Free ebook, Machine Learning, Python

• State of Data Science and Machine Learning 2020: 3 Key Findings - Dec 15, 2020.
  
  Kaggle recently released its State of Data Science and Machine Learning report for 2020, based on compiled results of its annual survey. Read about 3 key findings in the report here.

  Data Science, Kaggle, Machine Learning, Survey

• 6 Things About Data Science that Employers Don’t Want You to Know - Dec 14, 2020.
  
  As is the potential for any "trending hot" career, the reality of a position in the field may not be all that you initially expected. Data Science is no exception, and being still a young field, its evolving definition can offer some surprises that you should know about before accepting that dream offer.

  Business, Career Advice, Communication, Data Science, Data Scientist, SQL

• Data Science Volunteering: Ways to Help - Dec 11, 2020.
  
  No matter the field in which you hold some expertise, sharing your skills to benefit the lives of others or supporting non-profit organizations that try to make the world a better place is a noble and time-worthy personal pursuit. Many opportunities exist in data science to contribute to meaningful projects and crucial needs from your local community to a global scale.

  Alteryx, Data Science, Social Good

• R or Python? Why Not Both? - Dec 9, 2020.
  
  Do you use both R and Python, either in different projects or in the same? Check out prython, an IDE designed to handle your needs.

  Data Analysis, Data Science, IDE, Programming, Python, R

• 20 Core Data Science Concepts for Beginners - Dec 8, 2020.
  
  With so much to learn and so many advancements to follow in the field of data science, there are a core set of foundational concepts that remain essential. Twenty of these ideas are highlighted here that are key to review when preparing for a job interview or just to refresh your appreciation of the basics.

  Beginners, Bias, Cross-validation, Data Science, Data Visualization, Data Wrangling, Outliers, PCA, Variance

• 5 Free Books to Learn Statistics for Data Science - Dec 8, 2020.
  
  Learn all the statistics you need for data science for free.

  Data Science, Free ebook, Statistics

• Essential Math for Data Science: Probability Density and Probability Mass Functions - Dec 7, 2020.
  
  In this article, we’ll cover probability mass and probability density function in this sample. You’ll see how to understand and represent these distribution functions and their link with histograms.

  Data Science, Mathematics, Probability, Statistics

• AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2020 and Key Trends for 2021 - Dec 3, 2020.
  
  2020 is finally coming to a close. While likely not to register as anyone's favorite year, 2020 did have some noteworthy advancements in our field, and 2021 promises some important key trends to look forward to. As has become a year-end tradition, our collection of experts have once again contributed their thoughts. Read on to find out more.

  2021 Predictions, AI, Ajit Jaokar, Analytics, Brandon Rohrer, Daniel Tunkelang, Data Science, Deep Learning, Machine Learning, Pedro Domingos, Predictions, Research, Rosaria Silipo

• Introduction to Data Engineering - Dec 3, 2020.
  
  The Q&A for the most frequently asked questions about Data Engineering: What does a data engineer do? What is a data pipeline? What is a data warehouse? How is a data engineer different from a data scientist? What skills and programming languages do you need to learn to become a data engineer?

  Analytics, Data Engineer, Data Engineering, Data Science, Skills

• 10 Python Skills for Beginners - Dec 3, 2020.
  
  Python is the fastest growing, most-beloved programming language. Get started with these Data Science tips.

  Data Science, Programming, Python, Tips

• NoSQL for Beginners - Dec 2, 2020.
  
  NoSQL can offer an advantage to those who are entering Data Science and Analytics, as well as having applications with high-performance needs that aren’t met by traditional SQL databases.

  Beginners, Data Science, Database, NoSQL

• 14 Data Science projects to improve your skills - Dec 1, 2020.
  
  There's a lot of data out there and so many data science techniques to master or review. Check out these great project ideas from easy to advanced difficulty levels to develop new skills and strengthen your portfolio.

  Data Exploration, Data Science, Data Science Skills, Data Visualization, Prediction, Project

• Object-Oriented Programming Explained Simply for Data Scientists - Dec 1, 2020.
  
  Read this simple but effective guide to start using Classes in Python 3.

  Data Science, Data Scientist, Explained, Programming, Python

• Data Science History and Overview - Nov 30, 2020.
  
  In this era of big data that is only getting bigger, a huge amount of information from different fields is gathered and stored. Its analysis and extraction of value have become one of the most attractive tasks for companies and society in general, which is harnessed by the new professional role of the Data Scientist.

  About Gregory Piatetsky, Data Science, Data Scientist, History, Python

• Better data apps with Streamlit’s new layout options - Nov 26, 2020.
  
  Introducing new layout primitives - including columns, containers and expanders!

  App, Data Science, Machine Learning, Streamlit

• Kubernetes vs. Amazon ECS for Data Scientists - Nov 19, 2020.
  
  In this article, we’ll look at two container management solutions — Kubernetes and Amazon Elastic Container Service (ECS) — from a perspective that makes sense for aspiring and current data scientists.

  Amazon, AWS, Containers, Data Science, Data Scientist, Kubernetes

• Hypothesis Vetting: The Most Important Skill Every Successful Data Scientist Needs - Nov 18, 2020.
  
  A well-thought hypothesis sets the direction and plan for a Data Science project. Accordingly, a hypothesis is the most important item for evaluating whether a Data Science project will be successful.

  Data Science, Data Science Skills, Data Scientist

• Is Data Science for Me? 14 Self-examination Questions to Consider - Nov 17, 2020.
  
  You are intrigued by this exciting new field of Data Science, and you think you want in on the action. The demand remains very high and the salaries are strong. Before taking the leap onto this path, these questions will help you evaluate if you are ready for the challenges and opportunities.

  Career Advice, Communication, Data Science, Data Science Skills, Jobs, Salary

• How to Get Into Data Science Without a Degree - Nov 16, 2020.
  
  Breaking into any new field or slogging through a career change is always a challenge, and requires focus and even a little grit. While transitioning to becoming a Data Scientist is no different, aspiring to this role is possible, even without a formal post-secondary degree, largely due to the vast amount of quality learning resources available today.

  Career Advice, Data Science, Online Education

• Top Python Libraries for Deep Learning, Natural Language Processing & Computer Vision - Nov 16, 2020.
  
  This article compiles the 30 top Python libraries for deep learning, natural language processing & computer vision, as best determined by KDnuggets staff.

  Computer Vision, Data Science, Deep Learning, Machine Learning, Neural Networks, NLP, Python

• How to Acquire the Most Wanted Data Science Skills - Nov 13, 2020.
  
  We recently surveyed KDnuggets readers to determine the "most wanted" data science skills. Since they seem to be those most in demand from practitioners, here is a collection of resources for getting started with this learning.

  Algorithms, Amazon, Apache Spark, AWS, Computer Vision, Data Science, Data Science Skills, Deep Learning, Docker, NLP, NoSQL, PyTorch, Reinforcement Learning, TensorFlow

• Free From MIT: Intro to Computational Thinking with Julia - Nov 12, 2020.
  
  Introduction to Computational Thinking with Julia, with Applications to Modeling the COVID-19 Pandemic is another freely-available offering from MIT's Open Courseware.

  Computer Science, COVID-19, Data Science, Julia, MIT

• Learn to build an end to end data science project - Nov 11, 2020.
  
  Appreciating the process you must work through for any Data Science project is valuable before you land your first job in this field. With a well-honed strategy, such as the one outlined in this example project, you will remain productive and consistently deliver valuable machine learning models.

  Data Preparation, Data Science, GitHub, Portfolio, Python, Regression, Salary

• Moving from Data Science to Machine Learning Engineering - Nov 10, 2020.
  
  The world of machine learning — and software — is changing. Read this article to find out how, and what you can do to stay ahead of it.

  Career Advice, Data Engineering, Data Science, Machine Learning, Machine Learning Engineer

• 5 Reasons Why Containers Will Rule Data Science - Nov 9, 2020.
  
  Historically, containers were a way to abstract a software stack away from the operating system. For data scientists, containers have historically offered few benefits.

  Containers, Data Science, Gigantum, Kubernetes

• My Data Science Online Learning Journey on Coursera - Nov 9, 2020.
  
  Check out the author's informative list of courses and specializations on Coursera taken to get started on their data science and machine learning journey.

  Coursera, Courses, Data Science, Data Science Education

• Pandas on Steroids: End to End Data Science in Python with Dask - Nov 6, 2020.
  
  End to end parallelized data science from reading big data to data manipulation to visualisation to machine learning.

  Dask, Data Science, Pandas, Python

• Essential data science skills that no one talks about - Nov 6, 2020.
  
  Old fashioned engineering skills are what you need to boost your data science career.

  Career Advice, Data Science, Data Science Skills

• The Best Data Science Certification You’ve Never Heard Of - Nov 4, 2020.
  
  The CDMP is the best data strategy certification you’ve never heard of. (And honestly, when you consider the fact that you’re probably working a job that didn’t exist ten years ago, it’s not surprising that this certification isn’t widespread just yet.)

  Career Advice, Certification, Data Science, Data Science Education

• 10 Principles of Practical Statistical Reasoning - Nov 3, 2020.
  
  Practical Statistical Reasoning is a term that covers the nature and objective of applied statistics/data science, principles common to all applications, and practical steps/questions for better conclusions. The following principles have helped me become more efficient with my analyses and clearer in my conclusions.

  Data Analysis, Data Quality, Data Science, Statistical Analysis, Statistics

• Stop Running Jupyter Notebooks From Your Command Line - Oct 28, 2020.
  
  Instead, run your Jupyter Notebook as a stand alone web app.

  App, Data Science, Docker, Jupyter, Python

• KDnuggets™ News 20:n41, Oct 28: Difference Between Junior and Senior Data Scientists; Ain’t No Such a Thing as a Citizen Data Scientist - Oct 28, 2020.
  
  The unspoken difference between junior and senior data scientists; Ain't No Such a Thing as a Citizen Data Scientist; How to become a Data Scientist: a step-by-step guide; Good-bye Big Data. Hello, Massive Data!; DeepMind Relies on this Old Statistical Method to Build Fair Machine Learning Models

  Big Data, Career Advice, Citizen Data Scientist, Computer Vision, Data Science, Data Scientist, DeepMind, Statistical Modeling

• Getting A Data Science Job is Harder Than Ever – How to turn that to your advantage - Oct 27, 2020.
  
  Although many aspiring Data Scientists are finding it is becoming more difficult to land a job than it was in previous years, understanding what has changed in the hiring landscape can be used to to your advantage in matching with the best organization for your goals and interests.

  Career Advice, Data Science, Jobs, LinkedIn

• Advice for Aspiring Data Scientists - Oct 27, 2020.
  
  Are you a student of some type asking how to get into Data Science? You've come to the right place. Read on for both common and less basic advice on entering the field and excelling in the profession.

  Career Advice, Data Science, Data Scientist

• How Automation Is Improving the Role of Data Scientists - Oct 26, 2020.
  
  Here is an overview of 5 ways that data automation will enhance how scientists spend their time and improve the results they get.

  Automated Data Science, Automation, Data Science, Data Scientist

• The unspoken difference between junior and senior data scientists - Oct 22, 2020.
  
  The unspoken difference between junior and senior data scientists? It’s not what you think.

  Career Advice, Data Science, Data Scientist

• 5 Must-Read Data Science Papers (and How to Use Them) - Oct 20, 2020.
  
  Keeping ahead of the latest developments in a field is key to advancing your skills and your career. Five foundational ideas from recent data science papers are highlighted here with tips on how to leverage these advancements in your work, and keep you on top of the machine learning game.

  Data Science, Machine Learning, P-value, Research, Software, Technical Debt, Transformer

• Data Science in the Cloud with Dask - Oct 20, 2020.
  
  Scaling large data analyses for data science and machine learning is growing in importance. Dask and Coiled are making it easy and fast for folks to do just that. Read on to find out how.

  Cloud, Dask, Data Science, Python

• How to ace the data science coding challenge - Oct 15, 2020.
  
  Preparing to interview for a Data Scientist position takes preparation and practice, and then it could all boil down to a final review of your skills. Based on personal experience, these tips on how to approach such a review will help you excel in the coding challenge project for your next interview.

  Beginners, Challenge, Data Science, Interview, Programming

• Free From MIT: Intro to Computational Thinking and Data Science - Oct 14, 2020.
  
  This free course from MIT will help in your transition to thinking computationally, and ultimately solving complex data science problems.

  Computer Science, Courses, Data Science, MIT, Python

• Goodhart’s Law for Data Science and what happens when a measure becomes a target? - Oct 14, 2020.
  
  When developing analytics and algorithms to better understand a business target, unintended biases can sneak in that ensure desired outcomes are obtained. Guiding your work with multiple metrics in mind can help avoid such consequences of Goodhart's Law.

  Advice, Chris Wiggins, Data Science, Ethics, Goodhart’s Law, Metrics, Social Good

• Software Engineering Tips and Best Practices for Data Science - Oct 13, 2020.
  
  Bringing your work as a Data Scientist into the real-world means transforming your experiments, test, and detailed analysis into great code that can be deployed as efficient and effective software solutions. You must learn how to enable your machine learning algorithms to integrate with IT systems by taking them out of your notebooks and delivering them to the business by following software engineering standards.

  Best Practices, Data Science, Software Engineering, Tips

• A step-by-step guide for creating an authentic data science portfolio project - Oct 7, 2020.
  
  Especially if you are starting out launching yourself as a Data Scientist, you will want to first demonstrate your skills through interesting data science project ideas that you can implement and share. This step-by-step guide shows you how to do go through this process, with an original example that explores Germany’s biggest frequent flyer forum, Vielfliegertreff.

  COVID-19, Data Preparation, Data Science, Germany, Portfolio, Travel, Web Scraping

• Understanding Transformers, the Data Science Way - Oct 1, 2020.
  
  Read this accessible and conversational article about understanding transformers, the data science way — by asking a lot of questions that is.

  Data Science, Neural Networks, NLP, Transformer

• The Best Free Data Science eBooks: 2020 Update - Sep 30, 2020.
  
  The author has updated their list of best free data science books for 2020. Read on to see what books you should grab.

  Books, Data Science, Free ebook, Probability, Programming, Statistics

• International alternatives to Kaggle for Data Science / Machine Learning competitions - Sep 29, 2020.
  
  While Kaggle might be the most well-known, go-to data science competition platform to test your skills at model building and performance, additional regional platforms are available around the world that offer even more opportunities to learn... and win.

  Competition, Data Science, Kaggle, Machine Learning

• The Online Courses You Must Take to be a Better Data Scientist - Sep 28, 2020.
  
  These select courses have proved to be precious online resources which helped make the author a better data scientist today.

  Courses, Data Science, Data Scientist, MOOC

• The Most Complete Guide to PyTorch for Data Scientists - Sep 24, 2020.
  
  All the PyTorch functionality you will ever need while doing Deep Learning. From an Experimentation/Research Perspective.

  Data Science, Data Scientist, Neural Networks, Python, PyTorch

• KDnuggets™ News 20:n36, Sep 23: New Poll: What Python IDE / Editor you used the most in 2020?; Automating Every Aspect of Your Python Project - Sep 23, 2020.
  
  New Poll: What Python IDE / Editor you used the most in 2020?; Automating Every Aspect of Your Python Project; Autograd: The Best Machine Learning Library You're Not Using?; Implementing a Deep Learning Library from Scratch in Python; Online Certificates/Courses in AI, Data Science, Machine Learning; Can Neural Networks Show Imagination?

  Automation, Certificate, Courses, Data Science, Deep Learning, DeepMind, Machine Learning, Neural Networks, Python

• New Poll: What Python IDE / Editor you used the most in 2020? - Sep 22, 2020.
  
  The latest KDnuggets polls asks which Python IDE / Editor you have used the most in 2020. Participate now, and share your experiences with the community.

  Data Science, Development, IDE, Poll, Programming, Python

• How to Effectively Obtain Consumer Insights in a Data Overload Era - Sep 17, 2020.
  
  Everybody knows how important is understanding your customer, but how to do that in an era of Information Overload?

  Analytics, Customer Analytics, Data Science

• Lessons From My First Kaggle Competition - Sep 14, 2020.
  
  How I chose my first Kaggle competition to enter and what I learned from doing it.

  Competition, Data Science, Kaggle

• Statistics with Julia: The Free eBook - Sep 14, 2020.
  
  This free eBook is a draft copy of the upcoming Statistics with Julia: Fundamentals for Data Science, Machine Learning and Artificial Intelligence. Interested in learning Julia for data science? This might be the best intro out there.

  Books, Data Science, Free ebook, Julia, Statistics

• Feature Engineering for Numerical Data - Sep 11, 2020.
  
  Data feeds machine learning models, and the more the better, right? Well, sometimes numerical data isn't quite right for ingestion, so a variety of methods, detailed in this article, are available to transform raw numbers into something a bit more palatable.

  Data Preparation, Data Science, Feature Engineering

• AI Papers to Read in 2020 - Sep 10, 2020.
  
  Reading suggestions to keep you up-to-date with the latest and classic breakthroughs in AI and Data Science.

  AI, Attention, Convolutional Neural Networks, Data Science, GANs, Neural Networks, Reformer, Research

• 6 Common Mistakes in Data Science and How To Avoid Them - Sep 10, 2020.
  
  As a novice or seasoned Data Scientist, your work depends on the data, which is rarely perfect. Properly handling the typical issues with data quality and completeness is crucial, and we review how to avoid six of these common scenarios.

  Advice, Data Quality, Data Science, Hyperparameter, Mistakes, Overfitting

• Let’s Be Honest: We’re Drowning in Data - Sep 10, 2020.
  
  The fields of Big Data, Data Analytics/Science, and Data Integration need to face a new truth: We are drowning in data, more and more so every second of every day.

  Big Data, Data Analytics, Data Science

• 4 Tools to Speed Up Your Data Science Writing - Sep 9, 2020.
  
  This article covers how you can achieve your writing goals with these 4 tools.

  Advice, Data Science, GitHub, Jupyter

• KDnuggets™ News 20:n34, Sep 9: Top Online Data Science Masters Degrees; Modern Data Science Skills: 8 Categories, Core Skills, and Hot Skills - Sep 9, 2020.
  
  Also: Creating Powerful Animated Visualizations in Tableau; PyCaret 2.1 is here: What's new?; How To Decide What Data Skills To Learn; How to Evaluate the Performance of Your Machine Learning Model

  Data Science, Data Science Skills, Data Visualization, Machine Learning, Master of Science, Modeling, Online Education, PyCaret, Tableau

• 9 Developing Data Science & Analytics Job Trends - Sep 7, 2020.
  
  With so much disruption in 2020 already, a recent report by Burtch Works looks ahead to next year and beyond, and shares insights about how today's hiring market trends may impact our work lives for years to come.

  Analytics, Burtch Works, Career, COVID-19, Data Science, Jobs, Trends

• Data Scientists think data is their #1 problem. Here’s why they’re wrong. - Sep 4, 2020.
  
  We tend to think it's all about the data. However, for real data science projects at real organizations in real life, there are more fundamental aspects to consider to do data science right.

  Business, Data Science, Mistakes, Problem Definition

• Top Online Masters in Analytics, Business Analytics, Data Science – Updated - Sep 1, 2020.
  
  We provide an updated list of best online Masters in AI, Analytics, and Data Science, including rankings, tuition, and duration of the education program.

  Data Analytics, Data Science, Education, Master of Science, MS in Analytics, MS in Data Science, Online Education

• Data is everywhere and it powers everything we do! - Aug 28, 2020.
  
  In this article I would like to focus on how companies can start their data-centric strategies and how to achieve success in their data transformation journeys. Have tried to share my thoughts why companies have to consider data at its epitome for their growth, for being competitive, for being smarter, innovative and be prepared for any unforeseen market surprises.

  Analytics, Business, Data Science

• How Data Science Is Keeping People Safe During COVID-19 - Aug 25, 2020.
  
  Data, and more importantly, the way people use it, is shaping and refining approaches to COVID-19 safety. Here's a closer look at how this is happening.

  Coronavirus, COVID-19, Data Science, Safety

• Data Science Tools Illustrated Study Guides - Aug 25, 2020.
  
  These data science tools illustrated guides are broken up into four distinct categories: data retrieval, data manipulation, data visualization, and engineering tips. Both online and PDF versions of these guides are available.

  Cheat Sheet, Data Preprocessing, Data Processing, Data Science, Data Science Tools, Data Visualization, Python, R, SQL

• Data Science Meets Devops: MLOps with Jupyter, Git, and Kubernetes - Aug 21, 2020.
  
  An end-to-end example of deploying a machine learning product using Jupyter, Papermill, Tekton, GitOps and Kubeflow.

  Data Science, DevOps, Jupyter, Kubeflow, Kubernetes, MLOps

• KDD-2020 (virtual), the leading conference on Data Science and Knowledge Discovery, Aug 23-27 – register now - Aug 18, 2020.
  
  Using an interactive VR platform, KDD-2020 brings you the latest research in AI, Data Science, Deep Learning, and Machine Learning with tutorials to improve your skills, keynotes from top experts, workshops on state-of-the-art topics and over 200 research presentations.

  ACM SIGKDD, COVID-19, Data Science, Deep Learning, KDD, KDD-2020, Machine Learning, Meetings, Research

• The List of Top 10 Lists in Data Science - Aug 14, 2020.
  
  The list of Top 10 lists that Data Scientists -- from enthusiasts to those who want to jump start a career -- must know to smoothly navigate a path through this field.

  Algorithms, Data Science, Data Science Skills, Datasets, Influencers, LinkedIn, Python, Top 10

• Bring your Pandas Dataframes to life with D-Tale - Aug 13, 2020.
  
  Bring your Pandas dataframes to life with D-Tale. D-Tale is an open-source solution for which you can visualize, analyze and learn how to code Pandas data structures. In this tutorial you'll learn how to open the grid, build columns, create charts and view code exports.

  Data Exploration, Data Science, Data Visualization, Pandas, Python

• Going Beyond Superficial: Data Science MOOCs with Substance - Aug 13, 2020.
  
  Data science MOOCs are superficial. At least, a lot of them are. What are your options when looking for something more substantive?

  Courses, Data Science, Machine Learning, MOOC

• Introduction to Statistics for Data Science - Aug 12, 2020.
  
  Statistics is foundational for Data Science and a crucial skill to master for any practitioner. This advanced introduction reviews with examples the fundamental concepts of inferential statistics by illustrating the differences between Point Estimators and Confidence Intervals Estimates.

  Beginners, Data Science, Statistics

• How Natural Language Processing Is Changing Data Analytics - Aug 12, 2020.
  
  As it becomes more prevalent, NLP will enable humans to interact with computers in ways not possible before. This new type of collaboration will allow improvements in a wide variety of human endeavors, including business, philanthropy, health, and communication.

  Data Analytics, Data Science, NLP

• Unit Test Your Data Pipeline, You Will Thank Yourself Later - Aug 11, 2020.
  
  While you cannot test model output, at least you should test that inputs are correct. Compared to the time you invest in writing unit tests, good pieces of simple tests will save you much more time later, especially when working on large projects or big data.

  Data Science, Pipeline, Programming

• Data Science Internship Interview Questions - Aug 11, 2020.
  
  Data science is an attractive field because not only is it lucrative, but you can have opportunities to work on interesting projects, and you’re always learning new things. If you're trying to get started from the ground up, then review this guide to prepare for the interview essentials.

  Data Science, Internship, Interview Questions

• HOSTKEY GPU Grant Program - Aug 10, 2020.
  
  The HOSTKEY GPU Grant Program is open to specialists and professionals in the Data Science sector performing research or other projects centered on innovative uses of GPU processing and which will glean practical results in the field of Data Science, with the objective of supporting basic scientific research and prospective startups.

  Data Science, GPU, Research

• The Uncommon Data Science Job Guide - Aug 7, 2020.
  
  With the job landscape in Data Science becoming hyper-competitive, there are clear strategies you can consider to find your way to snagging a position in the field.

  Career, Career Advice, Data Science, Jobs

• New Poll: Which Data Science Skills You Have and Which Ones You Want? Vote Now - Aug 5, 2020.
  
  Take part in the latest KDnuggets poll, and share your insights with the community. Which Data Science skills do you currently possess, and which are you looking forward to add or improve upon? Vote now!

  Career, Data Science, Data Science Skills, Poll, Skills

• 5 Apache Spark Best Practices For Data Science - Aug 4, 2020.
  
  Check out these best practices for Spark that the author wishes they knew before starting their project.

  Apache Spark, Best Practices, Data Science

• Know What Employers are Expecting for a Data Scientist Role in 2020 - Aug 3, 2020.
  
  The analysis is done from 1000+ recent Data scientist jobs, extracted from job portals using web scraping.

  Career Advice, Data Science, Data Scientist

• First Steps of a Data Science Project - Jul 29, 2020.
  
  Many data science projects are launched with good intentions, but fail to deliver because the correct process is not understood. To achieve good performance and results in this work, the first steps must include clearly defining goals and outcomes, collecting data, and preparing and exploring the data. This is all about solving problems, which requires a systematic process.

  Beginners, Data Exploration, Data Preparation, Data Science

• Labelling Data Using Snorkel - Jul 24, 2020.
  
  In this tutorial, we walk through the process of using Snorkel to generate labels for an unlabelled dataset. We will provide you examples of basic Snorkel components by guiding you through a real clinical application of Snorkel.

  Data Labeling, Data Science, Deep Learning, Machine Learning, NLP, Python

• Data Science MOOCs are too Superficial - Jul 20, 2020.
  
  Most massive open online courses are too superficial because they offer introductory-level courses. For in-depth knowledge, more is needed to increase your knowledge and expertise after establishing a foundation.

  Data Science, MOOC, Online Education

• Foundations of Data Science: The Free eBook - Jul 13, 2020.
  
  As has become tradition on KDnuggets, let's start a new week with a new eBook. This time we check out a survey style text with a variety of topics, Foundations of Data Science.

  Data Science, Free ebook

• Why Learn Python? Here Are 8 Data-Driven Reasons - Jul 10, 2020.
  
  Through this blog, I will list out the major reasons why you should learn Python and the 8 major data-driven reasons for learning it.

  Data Science, Programming, Programming Languages, Python

• A Layman’s Guide to Data Science. Part 3: Data Science Workflow - Jul 6, 2020.
  
  Learn and appreciate the typical workflow for a data science project, including data preparation (extraction, cleaning, and understanding), analysis (modeling), reflection (finding new paths), and communication of the results to others.

  Beginners, Data Science, Data Workflow, Sciforce, Workflow

• Data Cleaning: The secret ingredient to the success of any Data Science Project - Jul 1, 2020.
  
  With an uncleaned dataset, no matter what type of algorithm you try, you will never get accurate results. That is why data scientists spend a considerable amount of time on data cleaning.

  Data Cleaning, Data Preparation, Data Science, Outliers, Python

• Software engineering fundamentals for Data Scientists - Jun 30, 2020.
  
  As a data scientist writing code for your models, it's quite possible that your work will make its way into a production environment to be used by the masses. But, writing code that is deployed as software is much different than writing code for exploratory data analysis. Learn about the key approaches for making your code production-ready that will save you time and future headaches.

  Advice, Best Practices, Data Science, Programming, Software Engineering

• KDnuggets™ News 20:n25, Jun 24: PyTorch Fundamentals You Should Know; Free Math Courses to Boost Your Data Science Skills - Jun 24, 2020.
  
  A Classification Project in Machine Learning: a gentle step-by-step guide; Crop Disease Detection Using Machine Learning and Computer Vision; Bias in AI: A Primer; Machine Learning in Dask; How to Deal with Missing Values in Your Dataset

  Agriculture, Computer Vision, Courses, Data Science, Machine Learning, Mathematics, PyTorch, Tom Fawcett

• Five Cognitive Biases In Data Science (And how to avoid them) - Jun 12, 2020.
  
  Everyone is prey to cognitive biases that skew thinking, but data scientists must prevent them from spoiling their work. Learn more about five biases that can all too easily make your seemingly objective work become surprisingly subjective.

  Advice, Bias, Cognitive Bias, Confirmation Bias, Data Science

• Top 6 Reasons Data Scientists Should Know Java - Jun 12, 2020.
  
  There are many reasons why data scientists should learn Java. Read this overview of 6 specific reasons to help decide if Java might be right for your projects.

  Data Science, Data Scientist, Java

• 3 Key Data Science Questions to Ask Your Big Data - Jun 3, 2020.
  
  The process of understanding your data begins by asking 3 questions at the highest level, and then iteratively asking hundreds of cascading questions to get deeper insights.

  Big Data, Business, Customer Analytics, Data Science, Metrics

• Best GIS Courses in 2020 - May 27, 2020.
  
  Geographic Information Systems Analysis is the analysis of spatial relationships and patterns. Spatial components are being ingrained into society with the advent of the Internet of Things (IoT) in which more data can be connected and is likely to have a spatio-temporal component as well.

  Data Science, Geospatial, GIS, MOOC

• Appropriately Handling Missing Values for Statistical Modelling and Prediction - May 22, 2020.
  
  Many statisticians in industry agree that blindly imputing the missing values in your dataset is a dangerous move and should be avoided without first understanding why the data is missing in the first place.

  Advice, Analytics, Business Analytics, Data Preparation, Data Science, Data Scientist, Missing Values, Statistics

• Complex logic at breakneck speed: Try Julia for data science - May 20, 2020.
  
  We show a comparative performance benchmarking of Julia with an equivalent Python code to show why Julia is great for data science and machine learning.

  Benchmark, Data Science, Julia, numpy, Python

• Top 10 Data Visualization Tools for Every Data Scientist - May 5, 2020.
  
  At present, the data scientist is one of the most sought after professions. That’s one of the main reasons why we decided to cover the latest data visualization tools that every data scientist can use to make their work more effective.

  Data Science, Data Science Tools, Data Scientist, Data Visualization

• Outbreak Analytics: Data Science Strategies for a Novel Problem - Apr 30, 2020.
  
  You walk down one aisle of the grocery store to get your favorite cereal. On the dairy aisle, someone sick from COVID-19 coughs. Did your decision to grab your cereal before your milk possibly keep you healthy? How can these unpredictable, near-random choices be included in complex models?

  Alteryx, Coronavirus, COVID-19, Data Science, Data Visualization, Forecasting