- Cloud Computing, Data Science and ML Trends in 2020–2022: The battle of giants [Gold Blog]
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.
- How I Got 4 Data Science Offers and Doubled my Income 2 Months After Being Laid Off [Gold Blog]
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.
- Essential Math for Data Science: Information Theory [Silver Blog]
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.
- My Data Science Learning Journey So Far [Gold Blog]
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.
- 15 Free Data Science, Machine Learning & Statistics eBooks for 2021 [Platinum Blog]
We present a curated list of 15 free eBooks compiled in a single location to close out the year.
- State of Data Science and Machine Learning 2020: 3 Key Findings [Gold Blog]
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.
- R or Python? Why Not Both? [Silver Blog]
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 [Platinum Blog]
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.
- AI, Analytics, Machine Learning, Data Science, Deep Learning Research Main Developments in 2020 and Key Trends for 2021 [Silver Blog]
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 [Gold Blog]
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?
- NoSQL for Beginners [Silver Blog]
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.
- Object-Oriented Programming Explained Simply for Data Scientists [Gold Blog]
Read this simple but effective guide to start using Classes in Python 3.
- Is Data Science for Me? 14 Self-examination Questions to Consider [Silver Blog]
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 [Gold Blog]
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 [Gold Blog]
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 [Gold Blog]
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.
- Learn to build an end to end data science project [Gold Blog]
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.
- Pandas on Steroids: End to End Data Science in Python with Dask [Gold Blog]
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 [Gold Blog]
Old fashioned engineering skills are what you need to boost your data science career.
- The Best Data Science Certification You’ve Never Heard Of [Platinum Blog]
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.)
- Top Python Libraries for Data Science, Data Visualization & Machine Learning [Platinum Blog]
This article compiles the 38 top Python libraries for data science, data visualization & machine learning, as best determined by KDnuggets staff.