Complete Machine Learning In Python With Projects By Spotle.ai
Learn and apply all the machine learning techniques that will make your Data Science skillset complete. Learn hands-on with many examples and projects from the industry and academic leaders.
Updated on Apr, 2024
Language - English
Machine Learning,Artificial Intelligence,Data Analysis,Data Science and AI ML,Python
Lectures -59
Duration -6 hours
30-days Money-Back Guarantee
Get your team access to 10000+ top Tutorials Point courses anytime, anywhere.
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 the 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:
1. The principle of supervised and unsupervised learning and their difference.
2. 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.
3. How to choose the right set of algorithms to solve your problem statement.
Goals
What will you learn in this course:
At the end of this course you will learn,
- 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, KNN.
- Cluster Analysis such as K-means clustering, Hierarchical clustering.
- Factor Analysis and Structural Equation Modelling as BONUS.
- How to choose the right set of algorithms and applying them in real-life projects in Python.
- Lots of real life problem solving using Python programming language.
Prerequisites
What are the prerequisites for this course?
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. 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
eCourse Certificate
Use your certificate to make a career change or to advance in your current career.
Our students work
with the Best
Related Video Courses
View MoreAnnual Membership
Become a valued member of Tutorials Point and enjoy unlimited access to our vast library of top-rated Video Courses
Subscribe now
Online Certifications
Master prominent technologies at full length and become a valued certified professional.
Explore Now