- 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.
- Understanding Bias-Variance Trade-Off in 3 Minutes - Sep 11, 2020.
This article is the write-up of a Machine Learning Lighting Talk, intuitively explaining an important data science concept in 3 minutes.
- 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.
- If I had to start learning Data Science again, how would I do it? - Aug 19, 2020.
While different ways to learn Data Science for the first time exist, the approach that works for you should be based on how you learn best. One powerful method is to evolve your learning from simple practice into complex foundations, as outlined in this learning path recommended by a physicist who turned into a Data Scientist.
- 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.
- 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.
- Learn Data Science from Top Universities for Free - Jun 29, 2020.
Where to find free lectures, seminars and complete courses from the likes of MIT, Stanford and Harvard.
- How Much Math do you need in Data Science? - Jun 26, 2020.
There exist so many great computational tools available for Data Scientists to perform their work. However, mathematical skills are still essential in data science and machine learning because these tools will only be black-boxes for which you will not be able to ask core analytical questions without a theoretical foundation.
- Exploring the Real World of Data Science - Jun 26, 2020.
An article highlighting things I’ve learned in the real world about data science.
- 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
- KDnuggets™ News 20:n24, Jun 17: Easy Speech-to-Text with Python; Data Distributions Overview; Java for Data Scientists - Jun 17, 2020.
Also: Deploy a Machine Learning Pipeline to the Cloud Using a Docker Container; Five Cognitive Biases In Data Science (And how to avoid them); Understanding Machine Learning: The Free eBook; Simplified Mixed Feature Type Preprocessing in Scikit-Learn with Pipelines; A Complete guide to Google Colab for Deep Learning
- 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.
- 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.
- Fighting Disease with Data: Q&A with Epidemiologist Amrish Baidjoe - Jun 11, 2020.
Data science tools are powerful for investigating the current pandemic and other outbreaks, when accurate and actionable data are crucial. Epidemiologist and R Epidemics Consortium leader Amrish Baidjoe shared his insights into using data science to fight disease, from modeling to automation to new technologies.
- 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.
- Don’t Democratize Data Science - Jun 2, 2020.
A plethora of online courses and tools promise to democratize the field, but just learning a few basic skills does not a true data scientist make.
- Introduction to Pandas for Data Science - Jun 1, 2020.
The Pandas library is core to any Data Science work in Python. This introduction will walk you through the basics of data manipulating, and features many of Pandas important features.
- KDD-2020 – Virtual Only Conference, Aug 23-27 - May 29, 2020.
After much consideration, the General Chairs, Executive Committee and Organizing Committee for KDD 2020 have decided to take the conference fully virtual. Clear your calendar for August 23-27, 2020, and enjoy access to all the virtual content live and on demand the week of the event.
- 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.
- 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.
- 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.
- Analytic Professionals – Share your views: Participate in the 2020 Data Science Survey - May 12, 2020.
Analytics & data science professionals: take part now in the Rexer Analytics 2020 Data Science Survey and share your views.
- Data Scientists, Corporate Fortune Tellers - May 8, 2020.
I realized that from a corporate perspective, “fortune teller” was not entirely off from the role of a “data scientist”.
- 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.
- How use the Coronavirus crisis to kickstart your Data Science career - May 4, 2020.
As the global economy dwindles, tech companies are hiring en masse. Now is the time to get yourself noticed as a Data Scientist and try to land your dream job.
- 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?
- Exploring the Impact of Geographic Information Systems - Apr 30, 2020.
GIS has mostly been behind more popular buzzwords like machine learning and deep learning. GIS has always been around us in the background being used in government, business, medicine, real estate, transport, manufacturing etc.
- Five Cool Python Libraries for Data Science - Apr 30, 2020.
Check out these 5 cool Python libraries that the author has come across during an NLP project, and which have made their life easier.
- KDnuggets™ News 20:n17, Apr 29: The Super Duper NLP Repo; Free Machine Learning & Data Science Books & Courses for Quarantine - Apr 29, 2020.
Also: Should Data Scientists Model COVID19 and other Biological Events; Learning during a crisis (Data Science 90-day learning challenge); Data Transformation: Standardization vs Normalization; DBSCAN Clustering Algorithm in Machine Learning; Find Your Perfect Fit: A Quick Guide for Job Roles in the Data World
- How Data Scientists Can Train and Updates Models to Prepare for COVID-19 Recovery - Apr 28, 2020.
The COVID-19 pandemic has affected everything, and building predictions during this time is difficult. Data science teams need to update their models to prepare for the recovery, and know how to properly train 2020 data models to learn from the coronavirus anomaly.
- Learning during a crisis (Data Science 90-day learning challenge) - Apr 24, 2020.
How can you keep your focus and drive during a global crisis? Take on a 90-day learning challenge for data science and check out this list of books and courses to follow.
- Should Data Scientists Model COVID19 and other Biological Events - Apr 22, 2020.
Biostatisticians use statistical techniques that your current everyday data scientists have probably never heard of. This is a great example where lack of domain knowledge exposes you as someone that does not know what they are doing and are merely hopping on a trend.
- Free High-Quality Machine Learning & Data Science Books & Courses: Quarantine Edition - Apr 22, 2020.
If you find yourself quarantined and looking for free learning materials in the way of books and courses to sharpen your data science and machine learning skills, this collection of articles I have previously written curating such things is for you.
- Fast Track Your Data Science Career - Apr 21, 2020.
Earn a Master of Professional Studies in Data Analytics online through Penn State World Campus – and you can add in-demand skills to your wheelhouse while you continue to work.
- Dockerize Jupyter with the Visual Debugger - Apr 17, 2020.
A step by step guide to enable and use visual debugging in Jupyter in a docker container.
- Can Java Be Used for Machine Learning and Data Science? - Apr 14, 2020.
While Python and R have become favorites for building these programs, many organizations are turning to Java application development to meet their needs. Read on to see how, and why.
- Free Workshop Preview: Data Thinking with Martin Szugat - Apr 13, 2020.
As anticipation grows for Predictive Analytics World’s virtual conferences (PAW for Industry 4.0, PAW for Healthcare and Deep Learning World on 11-12 May 2020) and virtual workshops (13 May 2020), here is a chance to start familiarising yourself with the quality of the content and of the virtual networking. Gain an insight into how to apply design thinking for data science & analytics. Reserve your spot.
- Peer Reviewing Data Science Projects - Apr 13, 2020.
In any technical development field, having other practitioners review your work before shipping code off to production is a valuable support tool to make sure your work is error-proof. Even through your preparation for the review, improvements might be discovered and then other issues that escaped your awareness can be spotted by outsiders. This peer scrutiny can also be applied to Data Science, and this article outlines a process that you can experiment with in your team.
- KNIME Spring Summit Online Edition - Apr 10, 2020.
The KNIME Summits, in spring and fall, have been taking place since 2008 in Europe and the US. In light of the coronavirus, this year’s KNIME Spring Summit moved online. Not too late to participate: KNIME Spring Summit continues online. Check out the extended summit program now.
- Has AI Come Full Circle? A data science journey, or why I accepted a data science job - Apr 10, 2020.
Personal journeys in Data Science can vary greatly between individuals. Some are just getting starting and wading into this vast ocean of opportunity, and others have been involved during its decades-long evolution as a professional field. This review of a longer journey can provide a broader perspective of how you might fit into this interesting career.
- How Data Science Is Being Used to Understand COVID-19 - Apr 10, 2020.
Read this overview to gain an understanding of how data scientists are working hard to learn as much about COVID-19 as they can.
- 3 Best Sites to Find Datasets for your Data Science Projects - Apr 9, 2020.
When first learning data science, you will inevitably find yourself looking for more datasets to practice with. Here, we recommend the 3 best sites to find datasets to spark your next data science project.
- KDnuggets™ News 20:n14, Apr 8: Free Mathematics for Machine Learning eBook; Epidemiology Courses for Data Scientists - Apr 8, 2020.
Stop Hurting Your Pandas!; Python for data analysis... is it really that simple?!?; Introducing MIDAS: A New Baseline for Anomaly Detection in Graphs; Build an app to generate photorealistic faces using TensorFlow and Streamlit; 5 Ways Data Scientists Can Help Respond to COVID-19 and 5 Actions to Avoid
- A Layman’s Guide to Data Science. Part 2: How to Build a Data Project - Apr 2, 2020.
As Part 2 in a Guide to Data Science, we outline the steps to build your first Data Science project, including how to ask good questions to understand the data first, how to prepare the data, how to develop an MVP, reiterate to build a good product, and, finally, present your project.
- Why you should NOT use MS MARCO to evaluate semantic search - Apr 2, 2020.
If we want to investigate the power and limitations of semantic vectors (pre-trained or not), we should ideally prioritize datasets that are less biased towards term-matching signals. This piece shows that the MS MARCO dataset is more biased towards those signals than we expected and that the same issues are likely present in many other datasets due to similar data collection designs.
- Advice for a Successful Data Science Career - Mar 30, 2020.
This blog is meant to show that most everyone has had to expend quite a bit of effort to get where they are. They have to work hard, sometimes experience failure, show discipline, be persistent, be dedicated to their goals, and sometimes sacrifice or take risks.
- SIGKDD Community Impact Program (Deadline Jun. 15) - Mar 27, 2020.
SIGKDD is announcing a funding opportunity through its Community Impact Program.The goal of the program is to support projects that promote data science and help the data science community to grow, broaden, and diversify. Read more here.
- Making sense of ensemble learning techniques - Mar 26, 2020.
This article breaks down ensemble learning and how it can be used for problem solving.
- Diffusion Map for Manifold Learning, Theory and Implementation - Mar 25, 2020.
This article aims to introduce one of the manifold learning techniques called Diffusion Map. This technique enables us to understand the underlying geometric structure of high dimensional data as well as to reduce the dimensions, if required, by neatly capturing the non-linear relationships between the original dimensions.
- Improving the partnership between Data Science and IT - Mar 18, 2020.
Friction can quickly arise as a result of these separate workflows and priorities. Given their differences, how can data science and IT more seamlessly work together in building a model-driven organization?
- Scaling Your Data Strategy - Mar 17, 2020.
This article presents a particular vision for a cohesive data strategy for addressing large-scale problems with data-driven solutions, based on prior professional experiences.
- Covid-19, your community, and you — a data science perspective - Mar 11, 2020.
Let's talk about covid-19; the reality, the numbers, and the data science.
- The Berlin Rent Freeze: How many illegal overpriced offers can I find online? - Mar 10, 2020.
This post presents an analysis of Berlin online real estate listings, investigating a controversial law capping rents in the state, which went into effect on February 23. Are current landlords already respecting the new rent cap?
- 50 Must-Read Free Books For Every Data Scientist in 2020 - Mar 9, 2020.
In this article, we are listing down some excellent data science books which cover the wide variety of topics under Data Science.
- Resources for Women in AI, Data Science, and Machine Learning - Mar 8, 2020.
For the international women's day, we feature resources to help more women enter and succeed in AI, Big Data, Data Science, and Machine Learning fields.
- How do we Better Solve Analytics Problems? - Mar 4, 2020.
Problem definition and solution development are key ingredients of being a consultant. Structuring the problem definition phase is critical to project success but may seem like a creative process.
- The Augmented Scientist Part 1: Practical Application Machine Learning in Classification of SEM Images - Mar 3, 2020.
Our goal here is to see if we can build a classifier that can identify patterns in Scanning Electron Microscope (SEM) images, and compare the performance of our classifier to the current state-of-the-art.
- 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 2) - Mar 2, 2020.
We explain important AI, ML, Data Science terms you should know in 2020, including Double Descent, Ethics in AI, Explainability (Explainable AI), Full Stack Data Science, Geospatial, GPT-2, NLG (Natural Language Generation), PyTorch, Reinforcement Learning, and Transformer Architecture.
- Data Science Curriculum for self-study - Feb 26, 2020.
Are you asking the question, "how do I become a Data Scientist?" This list recommends the best essential topics to gain an introductory understanding for getting started in the field. After learning these basics, keep in mind that doing real data science projects through internships or competitions is crucial to acquiring the core skills necessary for the job.
- Python and R Courses for Data Science - Feb 26, 2020.
Since Python and R are a must for today's data scientists, continuous learning is paramount. Online courses are arguably the best and most flexible way to upskill throughout ones career.
- Probability Distributions in Data Science - Feb 26, 2020.
Some machine learning models are designed to work best under some distribution assumptions. Therefore, knowing with which distributions we are working with can help us to identify which models are best to use.
- KDnuggets™ News 20:n08, Feb 26: Gartner 2020 Magic Quadrant for Data Science & Machine Learning Platforms; Will AutoML Replace Data Scientists? - Feb 26, 2020.
This week in KDnuggets: The Death of Data Scientists - will AutoML replace them?; Leaders, Changes, and Trends in Gartner 2020 Magic Quadrant for Data Science and Machine Learning Platforms; Hand labeling is the past. The future is #NoLabel AI; The Forgotten Algorithm; Getting Started with R Programming; and much, much more.
- Learning from 3 big Data Science career mistakes - Feb 25, 2020.
Thinking of data science as merely a technical profession, like programming, may take you away from your goals. We explain big mistakes to avoid, including not understanding the 2 cultures of statistics, and not understanding the shift to industrial focus.