- KDnuggets™ News 21:n02, Jan 13: Best Python IDEs and Code Editors; 10 Underappreciated Python Packages for Machine Learning Practitioners - Jan 13, 2021.
Best Python IDEs and Code Editors You Should Know; 10 Underappreciated Python Packages for Machine Learning Practitioners; Top 10 Computer Vision Papers 2020; CatalyzeX: A must-have browser extension for machine learning engineers and researchers
- 5 Tools for Effortless Data Science - Jan 11, 2021.
The sixth tool is coffee.
- JupyterLab 3 is Here: Key reasons to upgrade now - Jan 8, 2021.
Read about these 3 reasons for checking out JupyterLab 3 today.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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 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.
- 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.
- 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.
- KDnuggets™ News 20:n47, Dec 16: A Rising Library Beating Pandas in Performance; R or Python? Why Not Both? - Dec 16, 2020.
Also: 10 Python Skills They Don't Teach in Bootcamp; Data Science Volunteering: Ways to Help; A Journey from Software to Machine Learning Engineer; Data Science and Machine Learning: The Free eBook
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 5 Free Books to Learn Statistics for Data Science - Dec 8, 2020.
Learn all the statistics you need for data science for free.
- 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.
- Accelerate Your Career in Data Science - Dec 3, 2020.
Fast-track your promotion with a degree in data science. The part-time Master of Science in Analytics allows you to balance your personal and professional life while mastering the cutting-edge technology defining the industry today.
- 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.
- 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?
- 10 Python Skills for Beginners - Dec 3, 2020.
Python is the fastest growing, most-beloved programming language. Get started with these Data Science 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.
- 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.
- 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 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.
- Cartoon: Thanksgiving and Turkey Data Science - Nov 26, 2020.
A classic KDnuggets Thanksgiving cartoon examines the predicament of one group of fowl Data Scientists.
- Better data apps with Streamlit’s new layout options - Nov 26, 2020.
Introducing new layout primitives - including columns, containers and expanders!
- How Data Professionals Can Add More Variation to Their Resumes - Nov 24, 2020.
This article presents seven ways data professionals can add variation to their resumes.
- The top courses for aspiring data scientists - Nov 19, 2020.
Here are four courses that can give you the necessary skills to lead businesses in the 21st century. All of them include Python programming as a course component. Most of them require an undergraduate knowledge of statistics, calculus, linear algebra, and probability, so we recommend checking your course of interest for the specifics.
- 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.
- Top KDnuggets tweets, Nov 11-17: Data Engineering – the Cousin of Data Science, is Troublesome - Nov 18, 2020.
Also 6 Things About #DataScience that Employers Don't Want You to Know; NLP - Zero to Hero with #Python #NLProc; 5 Tricky SQL Queries Solved - Explaining the approach to solving a few complex #SQL queries.
- 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.
- How to Future-Proof Your Data Science Project - Nov 18, 2020.
This article outlines 5 critical elements of ML model selection & deployment.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- KDnuggets™ News 20:n43, Nov 11: The Best Data Science Certification You’ve Never Heard Of; Essential data science skills that no one talks about - Nov 11, 2020.
The Best Data Science Certification You've Never Heard Of; Essential data science skills that no one talks about; Pandas on Steroids: End to End Data Science in Python with Dask; How to Build a Football Dataset with Web Scraping; 2 Coding-free Ways to Extract Content From Websites to Boost Web Traffic
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.)
- 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.
- Top 38 Python Libraries for Data Science, Data Visualization & Machine Learning - Nov 2, 2020.
This article compiles the 38 top Python libraries for data science, data visualization & machine learning, as best determined by KDnuggets staff.
- Stop Running Jupyter Notebooks From Your Command Line - Oct 28, 2020.
Instead, run your Jupyter Notebook as a stand alone web app.
- 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
- 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.
- 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.
- 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.
- 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.
- KDnuggets™ News 20:n40, Oct 21: fastcore: An Underrated Python Library; Goodhart’s Law for Data Science: what happens when a measure becomes a target? - Oct 21, 2020.
fastcore: An Underrated Python Library; Goodhart's Law for Data Science and what happens when a measure becomes a target?; Text Mining with R: The Free eBook; Free From MIT: Intro to Computational Thinking and Data Science; How to ace the data science coding challenge
- 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 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.
- 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.
- 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.
- 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.
- KDnuggets™ News 20:n39, Oct 14: A step-by-step guide for creating an authentic data science portfolio project; Strategies of Docker Images Optimization - Oct 14, 2020.
Learn how to create inspiring Data Science portfolio projects; How to optimize Docker images; How LinkedIn Uses Machine Learning in its Recruiter Recommendation Systems; Understand the Algorithms of Social Manipulation; and read the annotated Machine Learning research papers.
- SIAM launches activity group, publications for data scientists - Oct 13, 2020.
Data science community at SIAM continues to grow with a new journal, book series, and activity group.
- 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.
- How I Levelled Up My Data Science Skills In 8 Months - Oct 9, 2020.
Read how the author used their time to level up a variety of their data science skills over a short period of time, and learn how you could do the same.
- 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.
- KDnuggets™ News 20:n38, Oct 7: 10 Essential Skills You Need to Know to Start Doing Data Science; The Best Free Data Science eBooks: 2020 Update - Oct 7, 2020.
Also: Comparing the Top Business Intelligence Tools: Power BI vs Tableau vs Qlik vs Domo; 5 Concepts Every Data Scientist Should Know; Understanding Transformers, the Data Science Way; 10 Best Machine Learning Courses in 2020
- Data Science Minimum: 10 Essential Skills You Need to Know to Start Doing Data Science - Oct 1, 2020.
Data science is ever-evolving, so mastering its foundational technical and soft skills will help you be successful in a career as a Data Scientist, as well as pursue advance concepts, such as deep learning and artificial intelligence.
- 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.
- 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.
- Are Data Analytics and Data Science Two Separate Fields? - Sep 29, 2020.
How are the fields of Data Analytics and Data Science related? Read this post by John Thompson, author of the new Packt book "Building Analytics Teams" to gain an understanding of the link between the two.
- 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.
- 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.
- 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.
- 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?
- 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.
- 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?
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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
- What Does It Take to be a Successful Data Scientist? - Sep 8, 2020.
What is the right approach to earning your stripes and calling yourself a successful data scientist?
- 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.
- 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.
- The Most Important Data Science Project - Sep 4, 2020.
What is the project every data scientist must do?
- 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 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.
- Data Versioning: Does it mean what you think it means? - Aug 26, 2020.
Does data versioning mean what you think it means? Read this overview with use cases to see what data versioning really is, and the tools that can help you manage it.
- KDnuggets™ News 20:n33, Aug 26: If I had to start learning Data Science again, how would I do it? Must-read NLP and Deep Learning articles for Data Scientists - Aug 26, 2020.
If I had to start learning Data Science again, how would I do it? Must-read NLP and Deep Learning articles for Data Scientists; These Data Science Skills will be your Superpower; Accelerated Natural Language Processing: A Free Amazon Machine Learning University Course.
- 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.
- 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.
- 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.
- KDnuggets™ News 20:n32, Aug 19: The List of Top 10 Data Science Lists; Data Science MOOCs with Substance - Aug 19, 2020.
The List of Top 10 Lists in Data Science; Going Beyond Superficial: Data Science MOOCs with Substance; Introduction to Statistics for Data Science; Content-Based Recommendation System using Word Embeddings; How Natural Language Processing Is Changing Data Analytics
- 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.
- 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.
- 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.
- 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?
- 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.
- 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.
- 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 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.
- 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.
- 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.
- 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!
- KDnuggets™ News 20:n30, Aug 5: What Employers are Expecting of Data Scientist Role; I have a joke about… - Aug 5, 2020.
Know What Employers are Expecting for a Data Scientist Role in 2020; I have a joke about …; First Steps of a Data Science Project; Why You Should Get Google's New Machine Learning Certificate; Awesome Machine Learning and AI Courses
- Setting Up Your Data Science & Machine Learning Capability in Python - Aug 4, 2020.
With the rich and dynamic ecosystem of Python continuing to be a leading programming language for data science and machine learning, establishing and maintaining a cost-effective development environment is crucial to your business impact. So, do you rent or buy? This overview considers the hidden and obvious factors involved in selecting and implementing your Python platform.
- 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.
- 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.
- 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.
- Automating Security & Privacy Controls for Data Science & BI – Webinar - Jul 28, 2020.
Moving sensitive data to the Cloud introduces the possibility of exposing data teams to new levels of risk, making it challenging to manage and prepare sensitive data for data science and analytics. Join our live webinar, Automating Security & Privacy Controls for Data Science & BI, Aug 12 @ 1PM ET to learn how Immuta for Databricks enables you to maximize the value of your sensitive data.
- 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.
- KDnuggets™ News 20:n28, Jul 22: Data Science MOOCs are too Superficial; The Bitter Lesson of Machine Learning - Jul 22, 2020.
Data Science MOOCs are too Superficial; The Bitter Lesson of Machine Learning; Building a REST API with Tensorflow Serving (Part 1); 3 Advanced Python Features You Should Know; Understanding How Neural Networks Think;
- 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.
- Scale sensitive data science and analytics with confidence - Jul 16, 2020.
Listen to this on-demand webinar and hear how WorldQuant Predictive derives insights from building models on sensitive data while maximizing value and minimizing risk.
- KDnuggets™ News 20:n27, Jul 15: Great explanation of Calculus, the Key to Deep Learning; 8 data-driven reasons to learn Python - Jul 15, 2020.
We bring you free MIT courses on Calculus, which is the key to understanding Deep Learning - check this amazing explanation of an integral and dx; 8 data-driven reasons to learn Python; How to get and analyze Financial data with Python; Free ebook: The Foundations of Data Science and more.
- 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.
- 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.
- KDnuggets™ News 20:n26, Jul 8: Speed up Your Numpy and Pandas; A Layman’s Guide to Data Science; Getting Started with TensorFlow 2 - Jul 8, 2020.
Speed up your Numpy and Pandas with NumExpr Package; A Layman's Guide to Data Science. Part 3: Data Science Workflow; Getting Started with TensorFlow 2; Feature Engineering in SQL and Python: A Hybrid Approach; Deploy Machine Learning Pipeline on AWS Fargate
- 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.
- Data Scientists Have Developed a Faster Way to Reduce Pollution, Cut Greenhouse Gas Emissions - Jul 3, 2020.
Data science is helping with one of the world's most pressing issues. Read about an approach and specific steps being taken by data scientists to quickly reduce pollution and greenhouse gas emissions.
- 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.