Tutorialspoint

Celebrating 11 Years of Learning Excellence! Use: TP11

Machine Learning Using Python

person icon Dr. Prerna Agrawal

4.2

Machine Learning Using Python

"Unleashing Intelligence with Python and Machine Learning"

updated on icon Updated on Jun, 2025

language icon Language - English

person icon Dr. Prerna Agrawal

category icon Development ,Data Science,Machine Learning

Lectures -11

Duration -3 hours

Lifetime Access

4.2

price-loader

Lifetime Access

30-days Money-Back Guarantee

Training 5 or more people ?

Get your team access to 10000+ top Tutorials Point courses anytime, anywhere.

Course Description

This course serves as an introduction to the field of machine learning with a focus on implementation using Python programming language. Machine learning is a branch of artificial intelligence that enables systems to learn from data and make predictions or decisions without being explicitly programmed. Python has emerged as one of the most popular programming languages for machine learning due to its simplicity, versatility, and a rich ecosystem of libraries such as scikit-learn, Mlxtend, Pandas, Seaborn, SciPy etc.

Throughout this course, students will explore fundamental machine learning concepts, algorithms, and techniques, and gain hands-on experience in implementing them using Python. The course will cover topics including:

1.  Introduction to Machine Learning

2.  Data Cleaning using Python

· Creating a Data Frame

· Describing the Data

· Navigating Data frames

· Selecting Row Based Conditionals

· Replacing Values

· Renaming Columns

· Finding The Minimum, Maximum. Sum, Average, and Count

· Finding Unique Values

· Handling Missing Values

· Deleting a Column

· Deleting a Row

· Dropping Duplicate rows

· Group Rows by Values and Time

· Looping over a Column

· Applying a Function Over All Elements in a Column

· Applying a Function to Groups

· Concatenating Data Frames

· Merging Data Frames

Handling Numerical Data

· Rescaling a Feature

· Standardizing a Feature

· Transforming Features

· Detecting Outliers

· Handling Outliers

· Deleting Observations with Missing Values

Handling Categorical Data

· Encoding Ordinal Categorical Features

· Encoding Dictionaries of Features

3. Plotting and exploring Numerical Data and Categorical Data

· Box Plot

· Histogram

· Scatterplot

· Cross Tabulations

4. Training and modelling the data

· Splitting a dataset into training and validation sets

· K-fold cross-validation

· Bootstrap Sampling

5. Dimensionality Reduction using Feature Extraction

· Reducing Features using PCA

· Reducing Features using LDA

· Reducing Features using NMF

6. Supervised Algorithms for Classification

· KNN

· Decision Tree

· Random forest

· Support Vector Machine

· Naive Bayes

· Logistic Regression

7. Improving Performance of the Model with Ensembling Methods

· Ada Boost

· XG Boost

8. Evaluating Performance of the Model for Classification

· Confusion Matrix

· Kappa Score

· F – measure

· Accuracy

· Precision

· Recall

· ROC Curve

9. Regression

· Linear Regression

· Logistic Regression

· Evaluation with R2 score

10. Unsupervised Algorithms

Clustering

· K-means

· K-Medoids

· Hierarchical

Association Analysis

· Apriori Algorithm and Association Rules

By the end of this course, students will have a solid understanding of machine learning concepts and techniques, proficiency in implementing machine learning algorithms using Python, and the ability to apply machine learning to solve real-world problems. This course will empower students to pursue further studies or careers in the rapidly growing field of machine learning and artificial intelligence.

Goals

Understand the fundamental concepts of machine learning and its applications across various domains.

Learn the process of data preprocessing, including handling missing data, feature scaling, and encoding categorical variables.

Master a variety of supervised learning algorithms such as linear regression, logistic regression, decision trees, support vector machines, and KNN.

Explore unsupervised learning techniques including clustering, dimensionality reduction, and association rule learning.

Develop the ability to critically analyze and interpret machine learning results and make data-driven decisions.

Build a solid foundation for further studies or career advancement in the field of machine learning and artificial intelligence.


Prerequisites

Knowledge of Python Programming

Machine Learning Using Python

Curriculum

Check out the detailed breakdown of what’s inside the course

Course Structure

1 Lectures
  • play icon Course Structure 04:26 04:26

Introduction to Machine Learning

1 Lectures
Tutorialspoint

Data Wrangling

1 Lectures
Tutorialspoint

Data Visualization

1 Lectures
Tutorialspoint

Supervised Learning using Python

2 Lectures
Tutorialspoint

Enhancing the Performance with Feature Reduction and Ensembling Techniques

2 Lectures
Tutorialspoint

Enhancing the Performance with K-Fold Cross Validation and Boot Strap Sampling

1 Lectures
Tutorialspoint

Unsupervised Learning

2 Lectures
Tutorialspoint

Instructor Details

Dr. Prerna Agrawal

Dr. Prerna Agrawal

Myself Dr. Prerna Agrawal a professor with a passion for teaching students and shaping their careers in IT. I have more than 12+ years of teaching experience and have a specialization in Machine Learning, Data Science, Cloud Computing, Big Data, Mobile Technology, Databases etc. The teaching style for programming will be fully based on live practical demo sessions.

Learning with me will be fun, and the outcome will be that the student will be able to use the knowledge gained from real-time problems to obtain solutions.

The methodology used will be presentations, practical demos, practical exercises and case studies to be solved.

Course Certificate

Use your certificate to make a career change or to advance in your current career.

sample Tutorialspoint certificate

Our students work
with the Best

Related Video Courses

View More

Annual Membership

Become a valued member of Tutorials Point and enjoy unlimited access to our vast library of top-rated Video Courses

Subscribe now
Annual Membership

Online Certifications

Master prominent technologies at full length and become a valued certified professional.

Explore Now
Online Certifications

Talk to us

1800-202-0515