Learn Deep Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Autoencoders, and Reinforcement Learning
Learn Python, Jupyter, Linux, NumPy, SciPy, Scikit-learn, Pandas, Linear algebra, From Industry Experts. A foundation course for Machine Learning & Data Science
Learn Python foundations, Conditional Execution, Loops, Strings, Files, Lists, Tuples, Dictionaries, Jupyter and Linux from Industry Experts.
2 years degree program approved by UGC. Program managed by REVA Academy for Corporate Excellence in collaboration with CloudxLab
Welcome to the tutorial on Linux Basics.
As part of this Linux tutorial, you will learn how to work in Linux Console. Most of the command and concepts are same in other Unix based systems.
Whether you are building a server-side application, creating an API, working data science, Linux is a very important skill. With Linux, you can almost automate anything.
This tutorial is very hands-on, it would make you do things in real-time in CloudxLab.
Happy Learning!
Learn Python foundations, Conditional Execution, Loops, Strings, Files, Lists, Tuples, Dictionaries, Jupyter and Linux from Industry Experts.
In this chapter, we learn the basics of Big Data which include various concepts, use-cases and understanding of the eco-system.
This chapter doesn't require any knowledge of programming or technology. We believe it is very useful for every to learn the basics of Big Data. So, jump in!
Happy Learning!
Welcome to a course in Scala Foundations.
As part of this course, you will learn how to write programs using Scala.
Scala is a programming language like Java or Python. The syntax is much like Python while under the hood it compiles to Java. It also comes with both an interactive interpreter and a compiler.
Further, Scala is designed for scalable computing where the code could be sent to data and codes is also run in parallel.
Scala is used in the enterprise world and has gain a lot of traction.
MapReduce is Framework as well as a paradigm of computing. By the way of map-reduce, we are able to break-down complex computation into distributed computing.
As part of this chapter, we are going to learning how to build MapReduce programmes using Java.
Please make sure you work along with the course instead of just sitting back and watching.
Happy Learning!
