Machine Learning Course Description

Machine Learning Course Description

Before you start, let me give you an overview of what this series has to offer you. Our machine learning course series comprises of the following sections:-

  1. ML Environment Setup and Overview
  2. Jupyter Notebook: The Ultimate Guide
  3. Numpy
  4. Pandas
  5. Matplotlib
  6. Seaborn
  7. Sklearn
  8. Linear Regression
  9. Logistic Regression
  10. Decision Tree
  11. Random Forest
  12. Support Vector Machine
  13. K Nearest Neighbours
  14. Naive Bayes
  15. Hyperparameter Optimization for Model Tuning

We will try to be on exact topics which i.e. we will not go so much deep or so much Shallow, we will try to be in middle, but we will not leave you out of any knowledge which may give you problems in your life journey. We assure you that we will always take it easy for you in the whole machine learning course.

These are the things that you’ll learn in the course. This course is designed to quickly get you started with ML so you can create projects that’ll help you level up your resume. Hope you’ll have fun learning throughout the course :). Bon Voyage.


Complete Machine Learning Course RoadMap Video



Credits to Daniel Bourke


Also Read:


  • Machine Learning: A Gentle Introduction
    Introduction to Machine Learning Machine Learning is probably one of the most interesting and hyped branches of computer science. The thing that separates humans from machines is the fact that humans learn from their experiences. But is it possible to make a machine learn? And The answer is Yes! It is possible through Machine Learning….
  • Machine Learning Course Description
    Before you start, let me give you an overview of what this series has to offer you. Our machine learning course series comprises of the following sections:- ML Environment Setup and Overview Jupyter Notebook: The Ultimate Guide Numpy Pandas Matplotlib Seaborn Sklearn Linear Regression Logistic Regression Decision Tree Random Forest Support Vector Machine K Nearest…
  • ML Environment Setup and Overview
    Introduction to Machine Learning In this article, you will learn about the ML Environment Setup, Machine Learning terminology, its paradigms, and a tutorial to help you set up your machine so you can code what you learn. Before we start with our ML Environment Setup, read this article to get an overview of machine learning….
  • Jupyter Notebook: The Ultimate Guide
    Introduction to Jupyter Notebook Whenever one starts programming the first aim of that person is to find an IDE that suits his/her needs. In ML there are times when you’ll want to keep a check on your data after doing a change. But in code editors like Vim, Vscode, etc. you have to run your…
  • Numpy For Machine Learning: A Complete Guide
    Up until now you’ve learned about the general idea of what ML does, set up your environment, and got to know about the working of your coding environment i.e. Jupyter Notebook. In this section, you’ll learn about a very powerful library called Numpy. We’ll learn about Numpy Array(np array for short) and operations on them,…
  • Python Pandas Tutorial: A Complete Introduction for Beginners
    In the previous section, we learned about Numpy and how we can use it to load, save, and pre-process data easily by using Numpy Arrays. Now Numpy is a great library to do data preprocessing but I’d like to tell you all about another wonderful Python library called Pandas. At the end of this tutorial,…
  • Matplotlib Python: A Beginner’s Walkthrough
    We know how to analyze data by analyzing the statistics of the data and we’ve learned how to manipulate the data. But is statistics enough to analyze the data? Short answer, Visualization of data is necessary in order to find details that we missed that’s why Matplotlib Python is the best library to visualize data…
  • Seaborn: Create Elegant Plots
    In the previous tutorial, we learned why data visualization is important and how we can create plots using matplotlib. In this tutorial, we’ll learn about another data visualization library called Seaborn, which is built on top of matplotlib. But why do we need seaborn if we have matplotlib? Using seaborn you can make plots that…
  • Set up Python Environment
    Now, it’s time to install the tools that we will use to write programs. So, we will be learning to Set up Python Environment in this article. Let’s start. 1. Installing Python first. First, we need to go to the official site of python: https://www.python.org/ Now we need to go to the downloads page of…
  • Linear Regression: Your 1st Step in Machine Learning
    Hi guys! So until now, we’ve learned about how we can use libraries to play with data. We did data analysis on a real dataset and we also learned how to visualize data. But what was the purpose behind it? Why do so many things? What are we trying to achieve? I’ll tell you all…

Share:

Author: Ayush Purawr