Complete Machine Learning In Python With Projects
Learn the essentials of machine-learning techniques with hands-on examples and projects from industry experts
Updated on Sep, 2024
Language - English
Development ,Data Science,Python
Lectures -59
Duration -6 hours
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Course Description
Machine learning, Data Science and Python have become key industry drivers in the global job and opportunity market. This course, designed and delivered by industry experts and Ivy League academic leaders, will help you learn machine learning from scratch. You will learn the subject with lots of applications and coding using Python programming language in real-life business scenarios.
In this course, you will learn:
- The principle of supervised and unsupervised learning and their difference.
- Linear Regression, Logistic Regression, Decision Tree, Regression Tree, Random Forest, Discriminant Analysis, Support Vector Machines, Naïve Bayes Classifier, KNN, Cluster Analysis, K-means clustering, Hierarchical clustering, Factor Analysis with lots of real-life examples using Python programming language.
- How to choose the right set of algorithms to solve your problem statement.
Goals
- The principle of supervised and unsupervised learning and their difference.
- Reinforcement learning as a BONUS.
- Regression models such as Linear Regression and Ridge Regression
- Classification models such as Decision Tree, Regression Tree, Random Forest, Logistic Regression, Discriminant Analysis, Support Vector Machines, Naïve Bayes Classifier, and KNN.
- Cluster Analysis such as K-means clustering and hierarchical clustering.
- Factor Analysis and Structural Equation Modelling as BONUS.
- How to choose the right set of algorithms and apply them in real-life projects in Python.
- Lots of real-life problem-solving using Python programming language.
Prerequisites
You are all set to start now if you just have a computer or a mobile handset with an internet connection.
Basic knowledge of Python will be a plus. A basic understanding of Statistics will be a plus.
Curriculum
Check out the detailed breakdown of what’s inside the course
Introduction
6 Lectures
-
Introduction
01:21
01:21
-
Supervised Machine Learning
04:57
04:57
-
Unsupervised Machine Learning
05:22
05:22
-
Difference Between Supervised And Unsupervised Machine Learning
02:38
02:38
-
Semi-supervised Machine Learning
03:40
03:40
-
BONUS - Reinforcement Learning
06:54
06:54
Installing Python
5 Lectures
Linear Regression With Python
5 Lectures
Logistic Regression With Python
5 Lectures
Complete Decision Tree With Python
10 Lectures
Regression Tree With Python
2 Lectures
Naïve Bayes Classifier And KNN With Python
5 Lectures
Random Forest With Python
4 Lectures
Discriminant Analysis With A Case Study
2 Lectures
Support Vector Machines With Python
4 Lectures
Ridge Regression
2 Lectures
K-means Clustering With Python
3 Lectures
Hierarchical Clustering With Case Studies
3 Lectures
BONUS - Understanding Factor Analysis
2 Lectures
BONUS - Understanding Structural Equation Modelling
1 Lectures
Instructor Details
Spotle Learn
Spotle Learn provides career ready courses in Artificial Intelligence, Data Science, Programming, Cloud Computing, IoT, Blockchain, AR and VR, Astronomy and Astrophysics and other in-demand skill areas. We have trained and certified over 100,000 people. Students from 2500 college campuses and leading corporates learn on Spotle to meet their career goals.
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