Machine Learning in Python for Absolute Beginners

你想知道机器学习算法是如何在 Python 中实现的吗？

在本课程中，您将了解机器学习以及如何利用 Python 构建可靠且高效的机器学习模型，从而为现实生活中的问题找到解决方案。我们将涵盖诸如准备数据集以训练机器学习模型以及在您的台式机和笔记本电脑上设置 Python 环境等方面。此外，您将学习如何利用这些库来评估和微调您的机器学习模型。

这个初学者程序将帮助任何想要快速开始研究机器学习解决方案的人。该计划将使用现实世界的问题教授概念。

让我们来看看我们将在本课程中涉及的主要主题！

Python机器学习简介

数据准备

分类模型的评估和调整

监督学习 – 回归和分类

在本课程中，我们将带您了解监督学习和无监督学习的主题。此外，您还将了解不同的算法，如回归、朴素贝叶斯、决策树、逻辑回归、随机森林、KNN 和支持向量机 (SVM)。

您将学习如何实施以下步骤以使用 Python 成功构建机器学习模型

安装 Python 和库

加载数据集

总结数据集

可视化数据集

评估一些算法

做一些预测

Published 09/2022
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 65 lectures (3h 24m) | Size: 3 GB

Learn the fundamentals of machine learning from ground up

What you’ll learn

Learn the basics of python programming language for machine learning
Learn to build machine learning models from scratch
Learn to build classification and regression solutions from ground up
Work on multiple real world projects

Requirements
Basic programming knowledge is must for taking the course

Description

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!

Who this course is for
Any one who wants to start learning machine learning will find this course very useful