Do You Want To Know How Machine Learning Algorithms Are Being Implemented In Python?
In this course, you'll learn about machine learning and how to utilize python for building reliable and efficient machine learning models to find solutions for real-life problems. We will be covering aspects like preparing data sets to train the machine learning models and setting up a python environment on your desktops and laptops. Also, you'll learn how to utilize these libraries to evaluate and fine-tune your machine learning models.
This beginner program will help anyone who wants to quickly start working on machine learning solutions. This program will teach the concepts using real-world problems.
Let's Have A Look At The Major Topics We'll Be Covering In This Course!
Introduction to Machine Learning with Python
Data Preparation
Evaluation and tuning of Classification Models
Supervised Learning - Regression and Classification
In this course, we'll take you through the topics of supervised learning and unsupervised learning. Also, you'll learn about the different algorithms like regression, naive Bayes, decision trees, logistic regression, random forest, KNN, and Support Vector Machines (SVM).
You'll be learning how to implement the following steps to successfully build machine learning models using Python
Installing the Python and libraries
Loading the dataset
Summarizing the dataset
Visualizing the dataset
Evaluating some algorithms
Making some predictions
Enroll today and learn the most in-demand skills of Python and machine learning
See You In The Class!