了解如何创建基于数据科学的算法。机器学习、深度学习和人工智能
你将学到什么
掌握 Python 机器学习 学习 Python
的基础知识
创建强大的机器学习模型
学习监督和非监督机器学习
进行强大的分析
处理强化学习、NLP 和深度学习等强大的主题 学习
使用不同的库进行数据分析
进入接触决策树
线性回归和逻辑回归
统计和概率
神经网络
要求
无需编程经验。但是，事先看过我们的 Python 课程可能会对您有所帮助。
能够下载文件
说明
在本课程中，作为初学者的您将以实践为导向的方式指导您在 Python 中学习算法和人工智能的所有相关领域，以便您最终可以使用 Python 3.9（最新版本）对您的 AI 进行编程) 没有错误。我们将在这里专注于机器学习和深度学习
本课程的讲师是 Vivien。
她从事 Python 和 Java 程序员工作 7 年，并在一家网络安全软件公司工作。在本课程中，Vivien 分享了她所知道的关于初学者成功开始机器学习并尽可能少犯错误所需知道的一切。Vivien 在本课程中的目标是为您提供强大的工具和 Python/机器学习的坚实基础，为您未来的编程体验奠定基础。这就是为什么该课程还依靠理论来使机器学习的基本概念易于理解，以便在本课程的后面应用它们。
机器学习课程涵盖了作为 Python 初学者和机器学习本身成功编写您的第一个程序和代码所需了解的所有内容。重点是实践，以便您可以在现实生活中主要使用 Python 的功能来解决您的问题并编写自己的机器学习代码，此外还有理论课。
Vivien 试图以这样一种方式设计课程，即使是 Python 的初学者也可以编写自己的算法。如果您想安全起见，请先查看 Python 课程，因为这是基本的编程语言。
我们将专注于所有重要的库、函数和学习方法，例如有监督和无监督机器学习。
我们还研究了深度学习、数据科学和 Python 本身等领域进一步编程的基础。
您想从头开始学习机器学习并编写自己的个人程序吗？
那我们课程见！
Learn how to create your Algorithms based on data science. Machine learning, deep learning and artificial intelligence
Genre: eLearning | MP4 | Video: h264, 1280×720 | Audio: AAC, 48.0 KHz
Language: English | Size: 2.21 GB | Duration: 4h 52m
What you’ll learn
Master Machine Learning on Python
Learn the basics of Python
Create robust Machine Learning models
Learn supervised and unsupervised machine learning
Make strong analysis
Handle powerful topics like Reinforcement Learning, NLP and Deep Learning
Learn to use different libraries for Data Analysis
Get in touch with Decision Trees
Linear Regression and Logistic Regression
Statistics and probability
Neural Networks
Requirements
No programming experience is required. However, having seen our Python course beforehand may help you.
Being able to download files
Description
In this course, you as a beginner will be guided through all relevant fields of Alorgythms and Artificial Intelligence in Python in a practice-oriented way, so that you can finally program your AI with Python 3.9 (the latest version) without errors. We’ll focus here on machine learning and deep Learning
Your lecturer in this course is Vivien.
She has been a Python and Java programmer for 7 years and works at a software company for cyber security. In this course, Vivien shares all she knows about what beginners need to know to get started successfully in machine learning and make as few mistakes as possible. Vivien’s goal in this course is to provide you with strong tools and a solid foundation in Python/Machine learning for your future programming experience. This is why the course also relies on theory to make the basic concepts of machine learning understandable in order to apply them later in this course.
The machine learning course covers everything you need to know as a beginner in Python and machine learning itself to successfully write your first programs and codes. The focus is on practice so that you can primarily use the functions of Python in real life to solve your problems and write your own machine-learning-code, in addition to theoretical lections.
Vivien tries to design the course in such a way that even total beginners to Python can program their own algorithms. If you want to be on the safe side, check out the Python course first, as this is the basic programming language.
We’ll focus on all the important libraries, functions, and learning methods like supervised and unsupervised machine learning.
We also look at the foundations for further programming in areas such as deep learning, data science, and Python itself.
You want to learn machine learning from scratch and code your own individual program?
See you in the course then!
Who this course is for
Beginner in the field of machine learning
Those who want to code their own AI
Those who would like to improve their Python skills
Those who are enthusiastic about mathematical models ?
原创文章，作者：steven，如若转载，请注明出处：https://rr3d.cn/30548.html
