A Training Program for beginners which covers the major difference between AI, ML and Deep Learning

By ridhigrg |Email | May 16, 2019 | 3342 Views

This Edureka Machine Learning tutorial (Machine Learning Tutorial with Python talks about the differences and relationship between AI, Machine Learning and Deep Learning. Below are the topics covered in this tutorial:

1. AI vs Machine Learning vs Deep Learning
2. What is Artificial Intelligence?
3. Example of Artificial Intelligence
4. What is Machine Learning?
5. Example of Machine Learning
6. What is Deep Learning?
7. Example of Deep Learning
8. Machine Learning vs Deep Learning

How does it work?
1. This is a 5 Week Instructor-led Online Course,40 hours of assignment and 20 hours of project work
2. We have a 24x7 One-on
One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. At the end of the training, you will be working on a real-time project for which we will provide you a Grade and a Verifiable Certificate!

About the Course
Edureka's Python Online Certification Training will make you an expert in Python programming. It will also help you learn Python the Big data way with integration of Machine learning, Pig, Hive, and Web Scraping through beautiful soup. During our Python Certification training, our instructors will help you:

1. Master the Basic and Advanced Concepts of Python
2. Understand Python Scripts on UNIX/Windows, Python Editors, and IDEs
3. Master the Concepts of Sequences and File operations
4. Learn how to use and create functions, sorting different elements, Lambda function, error handling techniques, and Regular expressions and using modules in Python
5. Gain expertise in machine learning using Python and build a Real Life Machine Learning application
6. Understand the supervised and unsupervised learning and concepts of Scikit-Learn
7. Master the concepts of MapReduce in Hadoop
8. Learn to write Complex MapReduce programs
9. Understand what is PIG and HIVE, Streaming feature in Hadoop, MapReduce job running with Python 
10. Implementing a PIG UDF in Python, Writing a HIVE UDF in Python, Pydoop and/Or MRjob Basics
11. Master the concepts of Web scraping in Python
12. Work on a Real Life Project on Big Data Analytics using Python and gain Hands-on Project Experience

Why learn Python?
Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built-in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations.

Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. 
Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. 

Source: HOB