AI and ML

Dealing with Missing Values in Python

Reading Time: 4 minutes For any Data Scientist, its very normal to deal with data sets having missing terms and still be able to manage and create a good predictive model out of it. Here we will discuss some techniques to handle missing data in a given data set. Missing Value occur when no data is stored for a variable or feature. It could be represented as “?”, “NA”, Continue Reading

AI: Right Structure of Agents For your Business

Reading Time: 5 minutes In the previous post, we discussed the environment in which the agent operates and the characteristics of those environments. In this post let us talk about the types of agents and challenges of data set for the agents. All agents have the same skeletal structure. They get percepts as inputs from the sensors and the actions are performed through the actuators. Now the agent can Continue Reading

MachineX: Ultimate guide to NLP (Part 1)

Reading Time: 7 minutes In this blog, we are going to see some basic text operations with NLP, to solve different problems. This Blog is a part of a series Ultimate guide to NLP , which will focus on Basic text pre-processing techniques. Some of the major areas that we will be covering in this series of Blogs include the following: Text Pre-Processing Understanding of Text & Feature Engineering Continue Reading

Data Lake – Build it in Phases

Reading Time: 3 minutes Data Lake – How to build a data lake and what are the phases involved in the same.