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所在平台: Udemy |
课程主页: https://www.udemy.com/course/deep-learning-recurrent-neural-networks-in-python/
课程评论：没有评论
课程名称：深度学习：Python中的循环神经网络 概述：***现已支持TensorFlow 2和Python 3***。你是否曾想过像OpenAI的ChatGPT、GPT-4、DALL-E、Midjourney和Stable Diffusion等AI技术是如何运作的？在本课程中，你将学习这些突破性应用的基础知识。课程重点介绍循环神经网络（RNN）这种强大的深度学习架构，其在序列建模中取得了最先进的结果，包括时间序列分析、预测和自然语言处理（NLP）。课程将说明为什么RNN比传统的机器学习算法（如隐马尔可夫模型）表现更好。 学习内容包括： - 机器学习和神经元的基础知识（简单回顾，帮助你热身！） - 用于分类和回归的神经网络（简单回顾，帮助你热身！） - 序列数据建模 - 时间序列数据建模 - 基于文本的数据建模（包括文本预处理步骤） - 使用TensorFlow 2构建RNN - 在TensorFlow 2中使用GRU和LSTM - 使用TensorFlow 2进行时间序列预测 - 使用LSTM在TensorFlow 2中预测股价和收益（提示：这不是你想的那样！） - 在TensorFlow 2中为NLP使用嵌入 - 为NLP构建文本分类RNN（示例：垃圾邮件检测、情感分析、词性标注、命名实体识别） 课程的所有材料均可免费下载和安装。我们将主要使用Numpy、Matplotlib和TensorFlow进行学习。讲师也会随时提供帮助，解答问题，支持你的数据科学之旅。该课程侧重于“如何构建和理解”，而不仅仅是“如何使用”。任何人都可以在阅读一些文档后在15分钟内学习如何使用API。这不仅仅是“记住事实”，而是通过实验“亲自去理解”。课程将教你如何可视化模型内部发生的情况。如果你想深入了解机器学习模型，而不仅仅是表面理解，这个课程就是为你准备的。 如同著名物理学家理查德·费曼所说：“我无法创造的东西，我就无法理解。” 我的课程是唯一能让你从零开始实现机器学习算法的课程。其他课程仅教你如何将数据插入库中，但你真的需要三行代码的帮助吗？在用十个数据集做同样的事情后，你会意识到你没有学到十件事，而是学到了一件事，只是重复了三行代码。 建议先修课程： - 矩阵加法、乘法 - 基本概率（条件和联合分布） - Python编程：if/else语句、循环、列表、字典、集合 - Numpy编程：矩阵和向量运算，加载CSV文件 如果你希望了解课程的学习顺序，可以查看“机器学习与AI的先修课程路线图”讲座（可在任何我的课程的常见问题解答中找到，包括免费的Numpy课程）。 独特特点： - 每一行代码都详细解释 - 如果你不同意随时可以发邮件给我 - 不浪费时间在键盘上“打字”，说实话，没有人能在20分钟内从零写出值得学习的代码 - 不惧怕大学级数学 - 提供其他课程忽略的重要算法细节
*** NOW IN TENSORFLOW 2 and PYTHON 3 ***Ever wondered how AI technologies like OpenAI ChatGPT, GPT-4, DALL-E, Midjourney, and Stable Diffusion really work? In this course, you will learn the foundations of these groundbreaking applications.Learn about one of the most powerful Deep Learning architectures yet!The Recurrent Neural Network (RNN) has been used to obtain state-of-the-art results in sequence modeling.This includes time series analysis, forecasting and natural language processing (NLP).Learn about why RNNs beat old-school machine learning algorithms like Hidden Markov Models.This course will teach you:The basics of machine learning and neurons (just a review to get you warmed up!)Neural networks for classification and regression (just a review to get you warmed up!)How to model sequence dataHow to model time series dataHow to model text data for NLP (including preprocessing steps for text)How to build an RNN using Tensorflow 2How to use a GRU and LSTM in Tensorflow 2How to do time series forecasting with Tensorflow 2How to predict stock prices and stock returns with LSTMs in Tensorflow 2 (hint: it's not what you think!)How to use Embeddings in Tensorflow 2 for NLPHow to build a Text Classification RNN for NLP (examples: spam detection, sentiment analysis, parts-of-speech tagging, named entity recognition)All of the materials required for this course can be downloaded and installed for FREE. We will do most of our work in Numpy, Matplotlib, and Tensorflow. I am always available to answer your questions and help you along your data science journey.This course focuses on "how to build and understand", not just "how to use". Anyone can learn to use an API in 15 minutes after reading some documentation. It's not about "remembering facts", it's about "seeing for yourself" via experimentation. It will teach you how to visualize what's happening in the model internally. If you want more than just a superficial look at machine learning models, this course is for you.See you in class!"If you can't implement it, you don't understand it"Or as the great physicist Richard Feynman said: "What I cannot create, I do not understand".My courses are the ONLY courses where you will learn how to implement machine learning algorithms from scratchOther courses will teach you how to plug in your data into a library, but do you really need help with 3 lines of code?After doing the same thing with 10 datasets, you realize you didn't learn 10 things. You learned 1 thing, and just repeated the same 3 lines of code 10 times...Suggested Prerequisites:matrix addition, multiplicationbasic probability (conditional and joint distributions)Python coding: if/else, loops, lists, dicts, setsNumpy coding: matrix and vector operations, loading a CSV fileWHAT ORDER SHOULD I TAKE YOUR COURSES IN?:Check out the lecture "Machine Learning and AI Prerequisite Roadmap" (available in the FAQ of any of my courses, including the free Numpy course)UNIQUE FEATURESEvery line of code explained in detail - email me any time if you disagreeNo wasted time "typing" on the keyboard like other courses - let's be honest, nobody can really write code worth learning about in just 20 minutes from scratchNot afraid of university-level math - get important details about algorithms that other courses leave out
