very comprehensive course.
Python Machine Learning and Data Science for Beginners
Machine Learning and Data Science for programming beginners using Python with scikit-learn, SciPy, Matplotlib, and Pandas
Updated on Sep, 2023
Language - English
Python Machine Learning and Data Science are crucial and this course will walk you through them. Machine Learning, Artificial Intelligence, and Deep Learning neural networks are the most frequently used terms and also the most muddled and misunderstood terms. Neural networks and machine learning are two subsets of the broad machine learning platform.
Python Machine Learning and Data Science for Beginners Overview
When we were young, we began to think logically about a variety of topics and to experience emotions, among other things. We persisted in thinking and came up with fixes for issues we encountered every day. The scientists working on deep learning neural networks are aiming towards that. a device that thinks.
Nonetheless, the primary area of focus in this course is machine learning. We are getting our machine ready for a prediction test during this course. It works exactly like how you would prepare for a maths exam in school or college. We develop our skills and practice ourselves by resolving as many similar mathematical puzzles as we can. Let's refer to these hypothetical examples of comparable issues and their solutions as the "Training Input" and "Training Output," respectively. And then the day of the test finally arrives. We will be given a brand-new set of issues to tackle, but they will be quite similar to the problems we learned. We must solve them based on our prior practice and learning experiences.
These issues might be referred to as "Testing Input" and our solutions as "Predicted Output." These responses will then be evaluated by our professor and compared to the actual responses, which we refer to as the "Test Output." Following that, a grade will be assigned based on the correct responses. We refer to this as our "Accuracy" mark. A machine learning engineer's and data scientist's livelihood is devoted to using various methods and evaluation criteria to increase this accuracy as much as feasible.
These are the main subjects covered in this course. Python is the programming language we are employing. Python is a fantastic tool for creating programs that analyze and predict data. It offers a ton of classes and features that carry out intricate mathematical analyses and provide solutions in straightforward one or two lines of code, allowing anyone to learn data science and machine learning without needing to be an expert statistician or mathematician. Python considerably streamlines the process.
What will you learn in this course:
Beginners who are interested in Machine Learning using Python
Learn fundamentals of machine learning and data science using Python
Develop the skills you need to apply machine learning and data science to real-world problems
Prepare for a career in machine learning or data science
Understand the scikit-learn machine learning library
Learn how data visualization works
Understand how natural language processing works
Understand how deep learning works
What are the prerequisites for this course?
- A medium-configuration computer and the willingness to indulge in the world of Machine Learning
Check out the detailed breakdown of what’s inside the course
- Course Overview & Table of Contents 09:08 09:08
- Introduction to Machine Learning - Part 1 - Concepts , Definitions and Types 04:37 04:37
- Introduction to Machine Learning - Part 2 - Classifications and Applications 05:54 05:54
System and Environment preparation
Learn Basics of python
Learn Basics of NumPy
Learn Basics of Matplotlib
Learn Basics of Pandas
CSV data file
Multivariate Dataset Visualization
Data Preparation (Pre-Processing)
Refresher Session - The Mechanism of Re-sampling, Training and Testing
Algorithm Evaluation Techniques
Algorithm Evaluation Metrics
Classification Algorithm Spot Check
Export, Save and Load Machine Learning Models
Quick Session: Imbalanced Data Set - Issue Overview And Steps
Iris Dataset : Finalizing Multi-Class Dataset
Finalizing a Regression Model - The Boston Housing Price Dataset
SOURCE CODE ATTACHED
I am a pioneering, talented and security-oriented Android/iOS Mobile and PHP/Python Web Developer Application Developer offering more than eight years’ overall IT experience which involves designing, implementing, integrating, testing and supporting impact-full web and mobile applications.
I am a Post Graduate Masters Degree holder in Computer Science and Engineering.
My experience with PHP/Python Programming is an added advantage for server based Android and iOS Client Applications.
User your certification to make a career change or to advance in your current career. Salaries are among the highest in the world.
Our students work
with the Best
Related Video CoursesView More
Become a valued member of Tutorials Point and enjoy unlimited access to our vast library of top-rated Video CoursesSubscribe now
Master prominent technologies at full length and become a valued certified professional.Explore Now