No Code And No Math Machine Learning

适合所有人的机器学习！谷歌顶点人工智能、数据机器人人工智能、显然人工智能、大机器学习、微软 Azure 和 Orange！

你将学到什么
构建机器学习模型以解决实际问题，无需任何代码和数学技能
使用应用于分类、回归和时间序列预测问题的主要工具
在以下工具中实施机器学习：Google Vertex AI，数据机器人 AI，很明显 AI，Big ML，Microsoft Azure 和 Orange
了解如何部署机器学习模型
要求
没有先决条件，但是如果您了解机器学习的基础知识，您会更喜欢它
无需编程或数学经验
描述
如果您想学习机器学习，但对编程或数学基础知识感到害怕，那么本课程适合您！您将学习如何使用六种不需要任何计算机编程或数学知识的工具来构建项目！本课程旨在让您快速轻松地创建动手项目，无需任何代码。它适合初学者，也适合需要提高生产力但又没有时间从头开始实现代码的中级或高级知识的学生。只需单击几下，您就可以执行探索性数据分析、构建、训练、测试并将机器学习模型投入生产！我们将介绍 6 种广泛用于商业项目的工具：Google Vertex AI、Data Robot AI、Abounce AI、大机器学习，Microsoft Azure 机器学习和 Orange！所有的项目都会从容的一步一步的开发，让你能充分利用内容。每个部分的末尾都有一个练习和解决方案，因此您可以练习每个工具的步骤！有超过30个讲座和5个小时的视频！

Published 9/2022
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.69 GB | Duration: 5h 6m

Machine learning for everyone! Google Vertex AI, Data Robot AI, Obviously AI, Big ML, Microsoft Azure and Orange!

What you’ll learn
Build machine learning models to use on real problems without a single line of code and no math skills
Use the main tools applied in classification, regression and time series forecasting problems
Implement machine learning in the following tools: Google Vertex AI, Data Robot AI, Obviously AI, Big ML, Microsoft Azure and Orange
Learn how to deploy machine learning models
Requirements
There are no prerequisites, however, you will enjoy it better if you know the basics of machine learning
No programming or math experience required
Description
If you want to learn machine learning but you feel intimidated by programming or math fundamentals, this course is for you!You are going to learn how to build projects using six tools that do not require any prior knowledge of computer programming or math! This course was designed for you to create hands-on projects quickly and easily, without a single line of code. It is suitable for beginners and also for students with intermediate or advanced knowledge, who need to increase productivity but at the same time do not have the time to implement code from scratch. You can perform exploratory data analysis, build, train, test and put machine learning models into production with a few clicks!We are going to cover 6 tools that are widely used for commercial projects: Google Vertex AI, Data Robot AI, Obviously AI, Big ML, Microsoft Azure Machine Learning, and Orange! All projects will be developed calmly and step by step, so that you can make the most of the content. There is an exercise along with the solution at the end of each section, so you can practice the steps for each tool! There are more than 30 lectures and 5 hours of videos!

Overview

Section 1: Introduction

Lecture 1 Course content

Lecture 2 Machine Learning – intuition

Lecture 3 Course materials

Section 2: Google Vertex AI

Lecture 4 Overview

Lecture 5 Datasets

Lecture 6 Training

Lecture 7 Regression metrics

Lecture 8 Deploy and predictions

Lecture 9 HOMEWORK

Lecture 10 Homework solution

Section 3: Data Robot AI

Lecture 11 Overview

Lecture 12 Datasets

Lecture 13 Classification metrics

Lecture 14 Training

Lecture 15 Deploy and predictions

Lecture 16 HOMEWORK

Lecture 17 Homework solution

Section 4: Obviously AI

Lecture 18 Overview

Lecture 19 Dataset, training, and predictions

Lecture 20 HOMEWORK

Lecture 21 Homework solution

Section 5: Big ML

Lecture 22 Overview

Lecture 23 Dataset

Lecture 24 Training and evaluating

Lecture 25 Predictions

Lecture 26 HOMEWORK

Lecture 27 Homework solution

Section 6: Microsoft Azure

Lecture 28 Overview

Lecture 29 Workspace and dataset

Lecture 30 Machine learning pipeline

Lecture 31 Evaluation and deploy

Lecture 32 Auto ML

Lecture 33 HOMEWORK

Lecture 34 Homework solution

Section 7: Orange

Lecture 35 Overview

Lecture 36 Classification

Lecture 37 Time series

Lecture 38 HOMEWORK

Lecture 39 Homework solution

Section 8: Final remarks

Lecture 40 Final remarks

People interested in building real machine learning models without a single line of code,People interested in starting their studies in Machine Learning and Data Science,Students who have little programming or math experience,Undergraduate and graduate students who are studying subjects related to the area of Artificial Intelligence