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所在平台: Udemy |
课程主页: https://www.udemy.com/course/neural-networks-in-python-a-guide-for-beginners/
课程评论：没有评论
课程名称：从头开始用Python构建神经网络：完整指南 课程概述：人工神经网络被认为是目前最有效的机器学习技术，谷歌、IBM和微软等公司以各种方式应用它们。自驾车、生成新歌曲、诗歌、图像甚至整个电影剧本的应用，均是基于神经网络构建的。虽然神经网络已经存在了一段时间，但随着深度学习的兴起，它们再次以更强大的形式回归，并被视为数据分析的最先进技术。然而，许多学习神经网络的学生面临的一个主要问题是缺乏易于理解的内容。大多数可用的学习材料都非常技术性，涉及许多数学公式，这使得希望初步了解该领域的学习者的学习过程变得极其困难。 本课程的主要目标是以简单而全面的方式呈现神经网络的理论和数学概念，即使您对神经网络一无所知，也能理解所有相关流程。我们将涵盖感知机、激活函数、多层网络、梯度下降和反向传播算法等概念，了解构建神经网络的基础。课程中还将使用Python逐步实现这些内容，而不使用任何特定于机器学习的Python库，目的是让您理解如何从零开始构建神经网络所需的全部计算。 总的来说，如果您希望在深度学习领域迈出第一步，这门课程将为您提供一切所需的重要知识。此外，课程内容将以相对较慢的速度进行讲解，确保初学者能够充分理解。如果您已经对神经网络有一定了解，这门课程也将帮助您复习和巩固一些重要概念。 准备好在职业生涯中迈出下一步了吗？期待在课程中见到您！
Artificial neural networks are considered to be the most efficient Machine Learning techniques nowadays, with companies the likes of Google, IBM and Microsoft applying them in a myriad of ways. You've probably heard about self-driving cars or applications that create new songs, poems, images and even entire movie scripts! The interesting thing about this is that most of these were built using neural networks. Neural networks have been used for a while, but with the rise of Deep Learning, they came back stronger than ever and now are seen as the most advanced technology for data analysis.One of the biggest problems that I've seen in students that start learning about neural networks is the lack of easily understandable content. This is due to the fact that the majority of the materials that are available are very technical and apply a lot of mathematical formulas, which simply makes the learning process incredibly difficult for whomever wishes to take their first steps in this field. With this in mind, the main objective of this course is to present the theoretical and mathematical concepts of neural networks in a simple yet thorough way, so even if you know nothing about neural networks, you'll understand all the processes. We'll cover concepts such as perceptrons, activation functions, multilayer networks, gradient descent and backpropagation algorithms, which form the foundations through which you will understand fully how a neural network is made. We'll also cover the implementations on a step-by-step basis using Python, which is one of the most popular programming languages in the field of Data Science. It's important to highlight that the step-by-step implementations will be done without using Machine Learning-specific Python libraries, because the idea behind this course is for you to understand how to do all the calculations necessary in order to build a neural network from scratch.To sum it all up, if you wish to take your first steps in Deep Learning, this course will give you everything you need. It's also important to note that this course is for students who are getting started with neural networks, therefore the explanations will deliberately be slow and cover each step thoroughly in order for you to learn the content in the best way possible. On the other hand, if you already know your way around neural networks, this course will be very useful for you to revise and review some important concepts.Are you ready to take the next step in your professional career? I'll see you in the course!
