- How Much Math do you need in Data Science? [Gold Blog]
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.
- Don’t Democratize Data Science [Gold Blog]
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.
- Top 10 Data Visualization Tools for Every Data Scientist [Silver Blog]
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.
- Five Cool Python Libraries for Data Science [Gold Blog]
Check out these 5 cool Python libraries that the author has come across during an NLP project, and which have made their life easier.
- Should Data Scientists Model COVID19 and other Biological Events [Silver Blog]
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 [Gold Blog]
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.
- Can Java Be Used for Machine Learning and Data Science? [Gold Blog]
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.
- Peer Reviewing Data Science Projects [Silver Blog]
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.
- Covid-19, your community, and you — a data science perspective [Gold Blog]
Let's talk about covid-19; the reality, the numbers, and the data science.
- 50 Must-Read Free Books For Every Data Scientist in 2020 [Silver Blog]
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 [Silver Blog]
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.
- 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 2) [Platinum Blog]
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.
- Python and R Courses for Data Science [Silver Blog]
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 [Silver Blog]
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.
- Learning from 3 big Data Science career mistakes [Gold Blog]
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.
- Free Mathematics Courses for Data Science & Machine Learning [Gold Blog]
It's no secret that mathematics is the foundation of data science. Here are a selection of courses to help increase your maths skills to excel in data science, machine learning, and beyond.
- 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 1) [Gold Blog]
2020 is well underway, and we bring you 20 AI, data science, and machine learning terms we should all be familiar with as the year marches onward.
- Fourier Transformation for a Data Scientist [Gold Blog]
The article contains a brief intro into Fourier transformation mathematically and its applications in AI.
- The Data Science Puzzle — 2020 Edition [Silver Blog]
The data science puzzle is once again re-examined through the relationship between several key concepts of the landscape, incorporating updates and observations since last time. Check out the results here.
- Data Validation for Machine Learning [Silver Blog]
While the validation process cannot directly find what is wrong, the process can show us sometimes that there is a problem with the stability of the model.
- Top 9 Mobile Apps for Learning and Practicing Data Science [Silver Blog]
This article will tell you about the top 9 mobile apps that help the user in learning and practicing data science and hence is improving their productivity.