[100% Off Udemy Course] Machine Learning Concepts and Application of ML using Python

  

Machine Learning Concepts and Application of ML using Python

Machine Learning Concepts and Application of ML using Python


 This Course Designed for Learn core concepts of Machine Learning. Apply ML techniques to real-world problems and develop AI/ML-based applications

  Uplatz offers this in-depth course on Machine Learning concepts and implementing machine learning with Python.

 

Objective: Learning basic concepts of various machine learning methods is a primary objective of this course. This a course specifically make student able to learn mathematical concepts, and algorithms used in machine learning techniques for solving real-world problems and developing new applications based on machine learning.

 

Course Outcomes: After completion of this course, student will be able to:

1. Apply machine learning techniques on real-world problem or to develop AI-based application

2. Analyze and Implement Regression techniques

3. Solve and Implement solution of Classification problem

4. Understand and implement Unsupervised learning algorithms

 

Topics

 

·         

Introduction of Python for ML, Python modules for ML, Dataset, Apply Algorithms on datasets, Result Analysis from dataset, Future Scope of ML.

 

·         

What is Machine Learning, Basic Terminologies of Machine Learning, Applications of ML, different Machine learning techniques, Difference between Data Mining and Predictive Analysis, Tools and Techniques of Machine Learning.

 

·         

Supervised Learning, Unsupervised Learning, Reinforcement Learning. Machine Learning Lifecycle.

 

·         

Classification: K-Nearest Neighbor, Decision Trees, Regression: Model Representation, Linear Regression.

 

·         

ClusteringK-Means Clustering, Hierarchical clustering, Density-Based Clustering.

 

 

Detailed Syllabus of Machine Learning Course

 

1. Linear Algebra

·         Basics of Linear Algebra

·         Applying Linear Algebra to solve problems

2. Python Programming

·         Introduction to Python

·         Python data types

·         Python operators

·         Advanced data types

·         Writing simple Python program

·         Python conditional statements

·         Python looping statements

·         Break and Continue keywords in Python

·         Functions in Python

·         Function arguments and Function required arguments

·         Default arguments

·         Variable arguments

·         Build-in functions

·         Scope of variables

·         Python Math module

·         Python Matplotlib module

·         Building basic GUI application

·         NumPy basics

·         File system

·         File system with statement

·         File a system with reading and writing

·         Random module basics

·         Pandas basics

·         Matplotlib basics

·         Building Age Calculator app

3. Machine Learning Basics

·         Get introduced to Machine Learning basics

·         Machine Learning basics in detail

4. Types of Machine Learning

·         Get introduced to Machine Learning types

·         Types of Machine Learning in detail

5. Multiple Regression

6. KNN Algorithm

·         KNN intro

·         KNN algorithm

·         Introduction to Confusion Matrix

·         Splitting dataset using TRAINTESTSPLIT

7. Decision Trees

·         Introduction to Decision Tree

·         Decision Tree algorithms

8. Unsupervised Learning

·         Introduction to Unsupervised Learning

·         Unsupervised Learning algorithms

·         Applying Unsupervised Learning

9. AHC Algorithm

10. K-means Clustering

·         Introduction to K-means clustering

·         K-means clustering algorithms in detail

11. DBSCAN

·         Introduction to DBSCAN algorithm

·         Understand DBSCAN algorithm in detail

·        DBSCAN program


What you Learn from this Course?

 

  1. Learn the A-Z of Machine Learning from scratch
  2. Build your career in Machine Learning, Deep Learning, and Data Science
  3. Become a top Machine Learning engineer
  4. Core concepts of various Machine Learning methods
  5. Mathematical concepts and algorithms used in Machine Learning techniques
  6. Solve real-world problems using Machine Learning
  7. Develop new applications based on Machine Learning
  8. Apply machine learning techniques on a real-world problem or to develop AI-based application
  9. Analyze and implement Regression techniques
  10. Linear Algebra basics
  11. A-Z of Python Programming and its application in Machine Learning
  12. Python programs, Matplotlib, NumPy, basic GUI application
  13. File system, Random module, Pandas
  14. Build Age Calculator app using Python
  15. Machine Learning basics
  16. Types of Machine Learning and their application in real-life scenarios
  17. Supervised Learning - Classification and Regression
  18. Multiple Regression
  19. KNN algorithm, Decision Tree algorithms
  20. Unsupervised Learning concepts & algorithms
  21. AHC algorithm
  22. K-means clustering & DBSCAN algorithm and program
  23. Solve and implement solutions of Classification problem
  24. Understand and implement Unsupervised Learning algorithms

 

 



Who can Enroll in this Course?

 

  1. Machine Learning Engineers & Artificial Intelligence Engineers
  2. Data Scientists & Data Engineers
  3. Newbies and Beginners aspiring for a career in Data Science and Machine Learning
  4. Machine Learning SMEs & Specialists
  5. Anyone (with or without data background) who wants to become a top ML engineer and/or Data Scientist
  6. Data Analysts and Data Consultants
  7. Data Visualization and Business Intelligence Developers/Analysts
  8. CEOs, CTOs, CMOs of any size organizations
  9. Software Programmers and Application Developers
  10. Senior Machine Learning and Simulation Engineers
  11. Machine Learning Researchers - NLP, Python, Deep Learning
  12. Deep Learning and Machine Learning enthusiasts
  13. Machine Learning Specialists
  14. Machine Learning Research Engineers - Healthcare, Retail, any sector
  15. Python Developers, Machine Learning, IoT, AirFlow, MLflow, Kubef
  16. Computer Vision / Deep Learning Engineers - Python

 

 

What will Requirement for this Course?

 

  1. Enthusiasm and determination to make your mark on the world!

                                                                             

How can Learn Course this Course?

1.    Create Account / Login on Udemy.com

2.    Learn Course by Enroll in this Course

         

Coupon Code for This Course:  ML_FULL_UPLATZ

 Enroll Here

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** Coupon Code Valid for Limited Time**

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