Artificial Intelligence 2021

我们将讨论不同类型的机器学习，机器学习中涉及的不同算法，包括分类算法、回归算法、聚类和关联算法。
为了更好地理解机器学习，我们将运行几个演示，我们将看到机器学习算法如何用于解决现实世界的问题。
之后我们将讨论机器学习的局限性以及为什么需要深度学习。我将向您介绍深度学习的概念，什么是神经元、感知器和多层感知器等等。我们将讨论不同类型的神经网络，并看看到底什么是反向传播，除此之外，我们将运行一个演示来更深入地了解深度学习。
我们将继续下一个模块，即自然语言处理。在自然语言处理下，我们将尝试了解什么是文本挖掘，NLP 中文本挖掘的区别，NLP 中的不同术语是什么，我们将通过使用 Python 实际实现 NLP 来结束会话。所以伙计们，这门课程有很多东西要讲。
本教程对于对本学科感兴趣或将此学科作为其课程一部分的研究生、研究生和研究生很有用。学习者可以是初学者或高级学习者。
本课程适用于谁：本教程将对对此主题感兴趣或将此主题作为课程一部分的毕业生、研究生和研究生有用。学习者可以是初学者或高级学习者

Created by Amer Mohammed | Published 1/2021
Duration: 2h 9m | 2 sections | 7 lectures | Video: 1280×720, 44 KHz | 555 MB
Genre: eLearning | Language: English + Sub

Machine Learning, Supervised Learning, un-supervised learning

What you’ll learn
This tutorial covers the basic/intermediate concepts of various fields of artificial intelligence like Artificial Neural Networks, Natural Language Processing, Machine Learning, Deep Learning, Genetic Algorithms etc., and its implementation in Python.

Requirements
Basic knowledge about Python programming. He/she should be aware about basic terminologies used in python packages
Description
We’ll discuss the different types of machine learning, the different algorithms involved in machine learning, which include classification algorithms, regression algorithms, clustering and association algorithms.
To make understand machine learning better, we’ll run a couple of demos where we will see how machine learning algorithms are used to solve real world problems.
After that we will discuss the limitations of machine learning and why deep learning is needed. i will introduce you to the deep learning concepts, what are neurons, perceptrons and multiple layer perceptrons and so on. we will discuss the different types of neural networks and also look at what exactly back propagation is, apart from this, we will be running a demo tounderstand deep learning in more depth.
We will move on to next module which is natural language processing. Under natural language processing we will try to understand what is text mining, the difference between text mining in NLP, what are the different terminologies in NLP and we will end the session by the practical implementation of NLP using Python. So guys there is a lot to cover in this course.
This tutorial will be useful for graduates, post graduates, and research students who either have an interest in this subject or have this subject as a part of their curriculum. The learner can be a beginner or an advanced learner.
Who this course is for:This tutorial will be useful for graduates, post graduates, and research students who either have an interest in this subject or have this subject as a part of their curriculum. The learner can be a beginner or an advanced learner