- Awesome Tricks And Best Practices From Kaggle - Apr 5, 2021.
Easily learn what is only learned by hours of search and exploration.
- What did COVID do to all our models? - Apr 2, 2021.
An interview with Dean Abbott and John Elder about change management, complexity, interpretability, and the risk of AI taking over humanity.
- What’s ETL? - Apr 2, 2021.
Discover what ETL is, and see in what ways it’s critical for data science.
- A/B Testing: 7 Common Questions and Answers in Data Science Interviews, Part 1 - Apr 1, 2021.
In this article, we’ll take an interview-driven approach by linking some of the most commonly asked interview questions to different components of A/B testing, including selecting ideas for testing, designing A/B tests, evaluating test results, and making ship or no ship decisions.
- Data vault: new weaponry in your data science toolkit - Mar 31, 2021.
Data Vault is a modern data modelling approach for capturing (historical) data in a structurally auditable and tractable way. While very helpful for data engineers, the Data Vault also enables Data Science in practice.
- Software Engineering Best Practices for Data Scientists - Mar 30, 2021.
This is a crash course on how to bridge the gap between data science and software engineering.
- How to break a model in 20 days — a tutorial on production model analytics - Mar 29, 2021.
This is an article on how models fail in production, and how to spot it.
- Overview of MLOps - Mar 26, 2021.
Building a machine learning model is great, but to provide real business value, it must be made useful and maintained to remain useful over time. Machine Learning Operations (MLOps), overviewed here, is a rapidly growing space that encompasses everything required to deploy a machine learning model into production, and is a crucial aspect to delivering this sought after value.
- The question that makes your data project more valuable - Mar 25, 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.
- 15 Habits I Learned from Highly Effective Data Scientists - Mar 24, 2021.
I’m using these habits in 2021 to become a more effective future data scientist.
- Top 10 Python Libraries Data Scientists should know in 2021 - Mar 24, 2021.
So many Python libraries exist that offer powerful and efficient foundations for supporting your data science work and machine learning model development. While the list may seem overwhelming, there are certain libraries you should focus your time on, as they are some of the most commonly used today.
- How to Succeed in Becoming a Freelance Data Scientist - Mar 23, 2021.
With recent growth in data science, now is the best time to get into freelancing. The following steps will help you get started with finding clients or help you improve your current strategy.
- Metric Matters, Part 2: Evaluating Regression Models - Mar 23, 2021.
In this second part review of the many options available for choosing metrics to evaluate machine learning models, learn how to select the most appropriate metric for your analysis of regression models.
- More Data Science Cheatsheets - Mar 18, 2021.
It's time again to look at some data science cheatsheets. Here you can find a short selection of such resources which can cater to different existing levels of knowledge and breadth of topics of interest.
- How to frame the right questions to be answered using data - Mar 18, 2021.
Understanding your data first is a key step before going too far into any data science project. But, you can't fully understand your data until you know the right questions to ask of it.
- KDnuggets™ News 21:n11, Mar 17: Is Data Scientist still a satisfying job? How To Overcome The Fear of Math and Learn Math For Data Science - Mar 17, 2021.
Must Know for Data Scientists and Data Analysts: Causal Design Patterns; Know your data much faster with the new Sweetviz Python library; The Inferential Statistics Data Scientists Should Know; Natural Language Processing Pipelines, Explained
- Are you satisfied in your job? Take our Data Community Job Satisfaction Survey - Mar 15, 2021.
The latest KDnuggets survey is looking to determine the job satisfaction levels of the data community. Take a few moments to contribute your answer and help paint a picture of the current situation.
- Forget Telling Stories; Help People Navigate - Mar 15, 2021.
When designing reporting & visualizations, think of them as part of a navigation framework rather than stand-alone information.
- Kedro-Airflow: Orchestrating Kedro Pipelines with Airflow - Mar 12, 2021.
The Kedro team and Astronomer have released Kedro-Airflow 0.4.0 to help you develop modular, maintainable & reproducible code with orchestration superpowers!
- Must Know for Data Scientists and Data Analysts: Causal Design Patterns - Mar 12, 2021.
Industry is a prime setting for observational causal inference, but many companies are blind to causal measurement beyond A/B tests. This formula-free primer illustrates analysis design patterns for measuring causal effects from observational data.
- A Machine Learning Model Monitoring Checklist: 7 Things to Track - Mar 11, 2021.
Once you deploy a machine learning model in production, you need to make sure it performs. In the article, we suggest how to monitor your models and open-source tools to use.
- How to Speed Up Pandas with Modin - Mar 10, 2021.
The Modin library has the ability to scale your pandas workflows by changing one line of code and integration with the Python ecosystem and Ray clusters. This tutorial goes over how to get started with Modin and how it can speed up your pandas workflows.
- KDnuggets™ News 21:n10, Mar 10: More Resources for Women in AI, Data Science, and Machine Learning; Speeding up Scikit-Learn Model Training - Mar 10, 2021.
More Resources for Women in AI, Data Science, and Machine Learning; Speeding up Scikit-Learn Model Training; Dask and Pandas: No Such Thing as Too Much Data; 9 Skills You Need to Become a Data Engineer; 8 Women in AI Who Are Striving to Humanize the World
- 8 Women in AI Who Are Striving to Humanize the World - Mar 8, 2021.
Some exceptional female researchers and engineers are working on projects to make the world a better place with the help of AI, data science, and machine learning.
- More Resources for Women in AI, Data Science, and Machine Learning - Mar 8, 2021.
Useful resources to help more women enter and succeed in AI, Data Science, and Machine Learning fields.
- KDnuggets™ News 21:n09, Mar 3: Top YouTube Channels for Data Science; Data Science Learning Roadmap for 2021 - Mar 3, 2021.
The top YouTube channels for Data Science; they will help you with Data Science Learning Roadmap for 2021; Another great learning option is Machine Learning Systems Design: A Free Stanford Course; and if you are still using pandas to process large datasets, here are two better options.
- 3 Mathematical Laws Data Scientists Need To Know - Mar 2, 2021.
Machine learning and data science are founded on important mathematics in statistics and probability. A few interesting mathematical laws you should understand will especially help you perform better as a Data Scientist, including Benford's Law, the Law of Large Numbers, and Zipf's Law.
- The Ultimate Guide to Acing Coding Interviews for Data Scientists - Mar 2, 2021.
This article covers understanding the 4 types of coding interview questions and preparing for them effectively.
- Top YouTube Channels for Data Science - Mar 1, 2021.
Have a look at the top 15 YouTube channels for data science by number of subscribers, along with some additional data on the channels to help you decide if they may have some content useful for you.
- Data Science Learning Roadmap for 2021 - Feb 26, 2021.
Venturing into the world of Data Science is an exciting, interesting, and rewarding path to consider. There is a great deal to master, and this self-learning recommendation plan will guide you toward establishing a solid understanding of all that is foundational to data science as well as a solid portfolio to showcase your developed expertise.
- 5 Supporting Skills That Can Help You Get a Data Science Job - Feb 25, 2021.
If you want to stand out among your fellow applicants, here are some supporting skills you should develop.
- The Difficulty of Graph Anonymisation - Feb 25, 2021.
Lessons from network science and the difficulty of graph anonymization. A data scientist's take on the difficultly of striking a balance between privacy and utility in anonymizing connected data.
- How Reading Papers Helps You Be a More Effective Data Scientist - Feb 24, 2021.
By reading papers, we were able to learn what others (e.g., LinkedIn) have found to work (and not work). We can then adapt their approach and not have to reinvent the rocket. This helps us deliver a working solution with lesser time and effort.
- Pandas Profiling: One-Line Magical Code for EDA - Feb 24, 2021.
EDA can be automated using a Python library called Pandas Profiling. Let’s explore Pandas profiling to do EDA in a very short time and with just a single line code.
- KDnuggets™ News 21:n08, Feb 24: Powerful Exploratory Data Analysis in just two lines of code; Cartoon: Data Scientist vs Data Engineer - Feb 24, 2021.
Powerful Exploratory Data Analysis in just two lines of code; Cartoon: Data Scientist vs Data Engineer; Evaluating Deep Learning Models: The Confusion Matrix, Accuracy, Precision, and Recall; Feature Store as a Foundation for Machine Learning; Approaching (Almost) Any Machine Learning Problem
- Data Observability, Part II: How to Build Your Own Data Quality Monitors Using SQL - Feb 23, 2021.
Using schema and lineage to understand the root cause of your data anomalies.
- People Skills for Analytical Thinkers - Feb 19, 2021.
Research shows that people skills are becoming more important with the rise of AI. A great way to boost these skills is by reading the new book: People Skills for Analytical Thinkers.
- 10 resources for data science self-study - Feb 17, 2021.
Many resources exist for the self-study of data science. In our modern age of information technology, an enormous amount of free learning resources are available to anyone, and with effort and dedication, you can master the fundamentals of data science.
- 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.
- Telling a Great Data Story: A Visualization Decision Tree - Feb 15, 2021.
Pick your visualizations strategically. They need to tell a story.
- 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.
- 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 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.
- KDnuggets™ News 21:n06, Feb 10: The Best Data Science Project to Have in Your Portfolio; Deep learning doesn’t need to be a black box - Feb 10, 2021.
The Best Data Science Project to Have in Your Portfolio; Deep learning doesn’t need to be a black box; Build Your First Data Science Application; How to create stunning visualizations using python from scratch; How to Get Your First Job in Data Science without Any Work Experience
- 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.
- 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?
- 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.
- 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.
- Build Your First Data Science Application - Feb 4, 2021.
Check out these seven Python libraries to make your first data science MVP application.
- How to Get Your First Job in Data Science without Any Work Experience - Feb 3, 2021.
Creativity, grit, and perseverance will become the three words you live by.
- Does Data Science Make You Happy? - Feb 2, 2021.
Maybe you are embarking on a new learning journey into the world of data and its analysis, or you already launched your career in the field. But, how can you make sure that data science is your calling? Indeed, if you feel good in your job, then you are likely on the right path.
- Celebrate International Women’s Day at the Women in Data Science (WiDS) Worldwide Virtual Conference - Feb 1, 2021.
On March 8, 2021, Stanford will host the inaugural 24-hour virtual Women in Data Science (WiDS) Worldwide conference. Find out speaker and registration information here.
- 3 Ways Understanding Bayes Theorem Will Improve Your Data Science - Feb 1, 2021.
Mastery of the mathematics and applications of this intuitive statistical concept will advance your credibility as a decision maker.
- 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.
- 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.
- 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.
- KDnuggets™ News 21:n04, Jan 27: The Ultimate Scikit-Learn Machine Learning Cheatsheet; Building a Deep Learning Based Reverse Image Search - Jan 27, 2021.
The Ultimate Scikit-Learn Machine Learning Cheatsheet; Building a Deep Learning Based Reverse Image Search; Data Engineering — the Cousin of Data Science, is Troublesome; Going Beyond the Repo: GitHub for Career Growth in AI & Machine Learning; Popular Machine Learning Interview Questions
- What to Learn to Become a Data Scientist in 2021 - Jan 26, 2021.
As data becomes the new ‘Gold’ for businesses, data scientists are set to find their value in this gold. This write-up clearly defines the job requirements and company expectations that this phenomenally evolving role entails.
- 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.
- 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.
- 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.
- How I Got 4 Data Science Offers and Doubled my Income 2 Months After Being Laid Off - Jan 19, 2021.
In this blog, I shared my story on getting 4 data science job offers including Airbnb, Lyft and Twitter after being laid off. Any data scientist who was laid off due to the pandemic or who is actively looking for a data science position can find something here to which they can relate.
- Data Science and Analytics Career Trends for 2021 - Jan 18, 2021.
Let's check out what are the new data science and analytics career trends for 2021 that may also shape the career options in the future.
- 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.
- Snowflake and Saturn Cloud Partner To Bring 100x Faster Data Science to Millions of Python Users - Jan 15, 2021.
Snowflake the cloud data platform, is partnering, integrating products, and pursuing a joint go-to-market with Saturn Cloud to help data science teams get 100x faster results. Read more about developments and how to get started here.
- 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.
- 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.
- 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.
- 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.
- 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.
- 5 Tricky SQL Queries Solved - Nov 12, 2020.
Explaining the approach to solving a few complex SQL queries.
- 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.