11
Mar
The world we live in is being transformed by data science quickly. Data science is becoming increasingly important because it enables businesses to use the information they collect to better their operations, develop new products and services, and enhance their decision-making process. Below are some of the industries that data science has been transforming recently:
28
Feb
This post will cover full-stack data science, analytics, Python, statistics, and data science courses as well as how to study data science from the beginning.
09
Feb
Usually, knowing what values you should use for the hyperparameters of a specific algorithm on a given dataset is challenging. That’s why you need to explore various strategies to tune hyperparameter values. With hyperparameter tuning, you can determine the right mix of hyperparameters that would maximize the performance of your model.
07
Feb
It’s normal today to talk about the massive computing power of supercomputers, the domain of data science that facilitates data availability and analysis, among others, and AI that can mimic mental actions similar to humans. But the road to the modern world’s AI, big data, and deep learning has been a long one. Let’s take a tour down the historical avenues to find how AI evolved into what it is today.
01
Feb
To become a data scientist, you should have knowledge of a variety of programming languages, which include Python, R, Java, SQL, JavaScript, C/C++, and Scala, to name a few. But why do you need to learn these programming languages? Let’s find out the answers by taking a look at the top programs you should learn to make your career path in data science a smooth-sailing one
30
Jan
According to the Stackoverflow community survey in 2022, the respondents were asked which database environments they have done extensive development work in over the past year, and which they want to work in over the next year. Even though below answers have a mingle of relational database management systems with the others, in this article, we will compare the top three RDBMS: Microsoft SQL, MySQL, and PostgreSQL.
24
Jan
The field of data science can play a crucial role in cybersecurity by helping to identify, analyze, and mitigate online threats. By leveraging data science techniques, organizations can analyze large datasets generated by network and security systems to identify patterns and anomalies that may indicate a potential threat. In this article, we will briefly discuss how data science can help in assuring security.
12
Jan
When the history of science is examined, it is seen that the need for scientific studies has increased over the ages as a result of societies’ desire for innovation and their desire to find different things.[1] Societies that have internalized scientific thinking and accepted it as a way of life; They have made significant progress in production, trade, quality of services and raising the welfare level of people. In the process of scientific development, each new knowledge has led to a rapid increase in the knowledge production process as a means of producing new knowledge.
06
Jan
Being good at math is an important skill for a data scientist to have, as data science involves the use of mathematical and statistical concepts and techniques to analyze and interpret data. However, the level of math proficiency required can vary depending on the specific role and responsibilities of a data scientist.
04
Jan
One day, K-means and LDA, two popular algorithms in natural language processing (NLP), decided to have a friendly competition to see which one was better at clustering and topic modeling. K-means, known for its simplicity and speed, boasted that it could group any collection of documents in a flash. LDA, on the other hand, was confident in its ability to uncover the latent topics hidden within the data using probabilistic generative modeling.