Recurrent neural networks (RNNs) are one of the states of the art algorithm in deep learning especially good for sequential data. It is used in many high-profile applications including Google’s…
Python’s Pandas library is the most widely used library in Python. Because this is the data manipulation library that is necessary for every aspect of data analysis or machine learning.…
Exploratory data analysis is very important to understanding a dataset properly. It is even important for machine learning. I have a few exploratory data analysis projects published before. But this…
The histogram is one of the most popular plots. It is useful to understand the overall distribution of a continuous variable. So, almost in any data analysis or exploratory data…
Convolutional Neural Network is a great tool for Image classification. It can perform other artificial intelligence tasks as well. But this article will focus primarily on image recognition. I have…
Matplotlib is arguably the most popular visualization library in Python. Also, some other higher-end libraries are also built on Matplotlib. I have a few articles on Matplotlib visualization techniques. Please…
The ‘tidyverse’ package in R is a very useful tool for data analysis in R as it covers almost everything you need to analyze a dataset. It is a combination…
Data visualization is probably the most widely used feature in data science for obvious reasons. Visualization is the best way to present and understand data. So, it is a good…
The Convolutional Neural Network (CNN) is a multi-layered neural network that is known to be able to detect patterns and complex features. It has been useful in face detection, self-driving cars, and a lot more very…
Data Visualization is the most effective way to communicate data to people, I believe. So, it is important for every data scientist or analyst to learn visualization. This article will share…