用Python从头开始构建自己的神经网络

Building your own Neural Network from Scratch with Python
通过实际例子掌握机器学习和深度学习算法和库是如何工作的。

你会学到什么
介绍Python，更高级的概念，如面向对象编程、装饰器、生成器，甚至像Numpy & Matplotlib这样的专用库
掌握机器学习和机器学习发展生命周期的基础。
线性回归、逻辑回归和从头开始构建的神经网络。
从基本原则构建简单的深度学习库

流派:电子学习| MP4 |视频:h264，1280×720 |音频:AAC，44.1 KHz
语言：英语+中英文字幕（云桥CG资源站 机译）|大小解压后:4.35 GB |时长:12h 28m

描述
我们将一起深入掌握机器学习和python编程中的概念，然后在不使用任何库的情况下，应用我们的知识从头开始构建我们自己的神经网络。

在本课程中，您将学到的知识不仅会为您的深度学习生涯打下坚实的基础，还会让您了解深度学习库是如何工作的。

如果你已经做到了这一点，这意味着你有兴趣掌握神经网络是如何工作的，并利用你的技能来解决实际问题。

您可能已经对机器学习和python编程有了一些了解，或者您可能是第一次接触这些知识。你来自哪一端并不重要，因为在本课程结束时，你将成为一名拥有丰富实践经验的专家。

如果你愿意在你的职业生涯中更进一步，这门课程是为你而设的，我们非常兴奋能帮助你实现目标！

这个课程是由Neuralearn提供给你的。

就像Neuralearn的其他课程一样，我们非常重视反馈。您在论坛中的评论和问题，将帮助我们更好地完成本课程。

欢迎在论坛上提出尽可能多的问题。我们尽最大努力在最短的时间内回复。

我们开始吧。

完成本课程后，您将掌握以下不同的概念。

机器学习基础。

基本的Python编程

基于任务的机器模型选择

批准错误

线性回归

逻辑回归

多类回归

神经网络

培训和优化

性能测定

验证和测试

用python从头开始构建机器学习模型。

过拟合和欠拟合

洗牌

集合

重量初始化

数据不平衡

学习速率衰减

正常化

超参数调谐

您还将获得:

终身学习本课程

在问答部分提供友好及时的支持

我的结业证书可供下载

30天退款保证

这门课是给谁上的:

初学Python的开发人员对深度学习很好奇。

深度学习实践者，他们希望掌握事物在幕后是如何运作的。

任何想掌握深度学习基础的人。

掌握深度学习库是如何工作的，并且是从头开始构建的。

享受吧！！！

这门课是给谁上的:
初学Python的开发人员对深度学习很好奇。
深度学习实践者，他们希望掌握幕后工作的方式
任何想掌握深度学习基础的人。
掌握深度学习库是如何工作的，并且是从头开始构建的。

Genre: eLearning | MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 4.2 GB | Duration: 12h 28m
Master how Machine Learning and Deep Learning algorithms and libraries work under the hood with practical examples.

What you’ll learn
Introductory Python, to more advanced concepts like Object Oriented Programming, decorators, generators, and even specialized libraries like Numpy & Matplotlib
Mastery of the fundamentals of Machine Learning and The Machine Learning Developmment Lifecycle.
Linear Regression, Logistic Regression and Neural Networks built from scratch.
Building a simple Deep Learning library from first principles

Description
Together we are going to master in depth concepts in machine learning and python programming, then apply our knowledge in building our own neural network from scratch without using any library.

What you’ll learn in this course will not only lay a solid foundation in your Deep Learning career, but also permit you to understand how deep learning libraries work.

If you’ve gotten to this point, it means you are interested in mastering how neural networks work and using your skills to solve practical problems.

You may already have some knowledge on Machine learning and python programming, or you may be coming in contact with these for the very first time. It doesn’t matter from which end you come from, because At the end of this course, you shall be an expert with much hands-on experience.

If you are willing to move a step further in your career, this course is destined for you and we are super excited to help achieve your goals!

This course is offered to you by Neuralearn.

And just like every other course by Neuralearn, we lay much emphasis on feedback. Your reviews and questions in the forum, will help us better this course.

Feel free to ask as many questions as possible on the forum. We do our very best to reply in the shortest possible time.

Let’s get started.

Here are the different concepts you’ll master after completing this course.

Fundamentals Machine Learning.

Essential Python Programming

Choosing Machine Model based on task

Error sanctioning

Linear Regression

Logistic Regression

Multi-class Regression

Neural Networks

Training and optimization

Performance Measurement

Validation and Testing

Building Machine Learning models from scratch in python.

Overfitting and Underfitting

Shuffling

Ensembling

Weight initialization

Data imbalance

Learning rate decay

Normalization

Hyperparameter tuning

YOU’LL ALSO GET:

Lifetime access to This Course

Friendly and Prompt support in the Q&A section

Udemy Certificate of Completion available for download

30-day money back guarantee

Who this course is for:

Beginner Python Developers curious about Deep Learning.

Deep Learning Practitioners who want gain a mastery of how things work under the hood.

Anyone who wants to master deep learning fundamentals.

Mastery of how Deep Learning libraries work and are built from scratch.

ENjoy!!!

Who this course is for:
Beginner Python Developers curious about Deep Learning.
Deep Learning Practitioners who want gain a mastery of how things work under the hood
Anyone who wants to master deep learning fundamentals.
Mastery of how Deep Learning libraries work and are built from scratch.

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