27 articles published
Are you planning to prepare yourself for Big Data interviews and become a successful Big Data Expert? You have landed on the right page. This article talks about the top interview questions so that you can mentally prepare answers for them. Excited? So let’s get started. Table of…
AutoML provides tools that automatically discover good machine learning model pipelines for a particular dataset without much user intervention. It is ideal for machine learning practitioners or domain experts new to machine learning to get quick and good results for a predictive modeling task.…
Ethical Hacking is a perfect career choice for those interested in communication, IT security, and problem-solving. This article aims at serving as a guide to become an ethical hacker. It includes detailed information about the field, an ethical hacker’s role, some of the skills required, and…
Who are non-technical people? Those without an engineering degree? The journey for these people to become a data scientist is not very different from the technical ones. To be in the Data Science Industry, one needs not to be a top-notch engineer with in-depth knowledge of complex topics but should…
Artificial Intelligence has an estimated market of 7.35 billion US dollars and is growing by leaps and bounds. As predicted by McKinsey, AI, including reinforcement learning and deep learning techniques, can create $3.5 to 5.8 trillion dollars across nine businesses in 19 industries. Machine…
A distinct discipline is emerging as the area of data science matures: data engineering. The importance of data engineers compared to data scientists is acknowledged by tech giants, including Facebook, Amazon, and Google. That’s why they recruit candidates with expertise such as data…
In machine learning, reducing dimensionality is a critical approach. Overfitting of the learning model may result in a large number of features available in the dataset. There are two standard dimensionality reduction techniques used by machine learning experts to evaluate the collection of…
A form of exploratory data analysis in which observations are divided into different groups with standard features is known as clustering analysis. The purpose of classification or cluster analysis is to ensure that different groups must have different observations as possible. The two main types…
Decision trees are part of the Supervised Classification Algorithm family. On classification issues, they work very well, the decisional route is reasonably easy to understand, and the algorithm is fast and straightforward. Random Forest is the ensemble variant of Decision Trees. Random forest is a…
Machine learning is nothing but a research field that allows computers without any specific programming to “learn” like humans. High-dimensionality statistics and dimensionality reduction techniques that have been used for data visualization. These techniques are applied in machine…
Naïve Bayes is a surprisingly powerful yet simple algorithm for predictive modeling. It is a machine learning model that can handle large volumes of data, including millions of data records. Naïve Bayes is the recommended approach for Natural Language Processing tasks such as sentiment analysis as…
Machine learning is a scientific technique where computers learn how to solve a problem without directly programming them. The ML race is currently led by deep learning fuelled by improved algorithms, computing power and big data. The classical algorithms of ML still have a firm place in the field.…