Giveaway [Udemy] Machine Learning with Python Training (beginner to advanced)

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Machine Learning with Python Training (beginner to advanced) | Udemy

Description
Machine Learning with Python - Course Syllabus
1. Introduction to Machine Learning
What is Machine Learning?
Need for Machine Learning
Why & When to Make Machines Learn?
Challenges in Machines Learning
Application of Machine Learning
2. Types of Machine Learning
Types of Machine Learning
      a) Supervised learning
      b) Unsupervised learning
      c) Reinforcement learning
Difference between Supervised and Unsupervised learning
Summary
3. Components of Python ML Ecosystem
Using Pre-packaged Python Distribution: Anaconda
Jupyter Notebook
NumPy
Pandas
Scikit-learn
4. Regression Analysis (Part-I)
Regression Analysis
Linear Regression
Examples on Linear Regression
scikit-learn library to implement simple linear regression
5. Regression Analysis (Part-II)
Multiple Linear Regression
Examples on Multiple Linear Regression
Polynomial Regression
Examples on Polynomial Regression
6. Classification (Part-I)
What is Classification
Classification Terminologies in Machine Learning
Types of Learner in Classification
Logistic Regression
Example on Logistic Regression
7. Classification (Part-II)
What is KNN?
How does the KNN algorithm work?
How do you decide the number of neighbors in KNN?
Implementation of KNN classifier
What is a Decision Tree?
Implementation of Decision Tree
SVM and its implementation
8. Clustering (Part-I)
What is Clustering?
Applications of Clustering
Clustering Algorithms
K-Means Clustering
How does K-Means Clustering work?
K-Means Clustering algorithm example
9. Clustering (Part-II)
Hierarchical Clustering
Agglomerative Hierarchical clustering and how does it work
Woking of Dendrogram in Hierarchical clustering
Implementation of Agglomerative Hierarchical Clustering
10. Association Rule Learning
Association Rule Learning
Apriori algorithm
Working of Apriori algorithm
Implementation of Apriori algorithm
11. Recommender Systems
Introduction to Recommender Systems
Content-based Filtering
How Content-based Filtering work
Collaborative Filtering
Implementation of Movie Recommender System
Who this course is for:
Data Scientists and Senior Data Scientists
Machine Learning Scientists
Python Programmers & Developers
Machine Learning Software Engineers & Developers
Computer Vision Machine Learning Engineers
Beginners and newbies aspiring for a career in Data Science and Machine Learning
Principal Machine Learning Engineers
Machine Learning Researchers & Enthusiasts
Anyone interested to learn Data Science, Machine Learning programming through Python
AI Specialists & Consultants
Python Engineers Machine Learning Ai Data Science
Data, Analytics, AI Consultants & Analysts
Machine Learning Analysts
This course includes:
24 hours on-demand video
19 downloadable resources
Full lifetime access
Access on mobile and TV
Certificate of completion

https://www.udemy.com/course/machine-lea...=ML_UPLATZ