Machine Learning courses

1656 Courses

AI TIME PhD ICLR专场七

参与AI TIME PhD ICLR专场七,探索人工智能研究的最新突破。这次中文会议由国际学习表征会议(ICLR)的博士生主讲,讲述关于人工智能和机器学习领域的尖端发展和创新方法。 本次会议为所有对人工智能、机器学习和计算机科学有兴趣的学者和研究人员提供了绝佳机会。您将获得权威的信息和见解,深入了解深度学习和神经网络方面的最新研究动向。 主办单位:学堂在线 (Xueta.
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算法支撑的赛博智能经济

加入我们,深入探讨由算法推动的赛博智能经济,获取关于计算智能和算法系统如何深刻改变现代经济结构和商业模式的宝贵见解。本次学术讲座由清华大学提供,通过XuetangX平台传播,适合人工智能课程和机器学习课程的爱好者。 讲座内容涵盖: 算法在经济中的应用 计算智能的最新发展 现代经济结构的转型 新商业模式的探讨 该讲座有助于您全面了解当前技术在经济领.
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人工智能基础核心技术之事件检测

欢迎参加由清华大学提供的“人工智能基础核心技术之事件检测”课程。在此课程中,您将学习如何运用人工智能中的事件检测技术来识别和分析数据流中的重大事件或模式。这是一门中文课程,旨在帮助您深入理解事件检测在人工智能中的应用。 本课程涵盖多个关键主题,包括人工智能、机器学习、计算机视觉、神经网络、时间序列分析、信号处理及模式识别。这为您在这些领域的进一.
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AI for Academic Search (人工智能助力学术搜索)

Unlock the potential of artificial intelligence in academic search and research discovery with this lecture from Tsinghua University. Delivered in Chinese, the session delves into how AI is revolutionizing the way scholars access and retrieve information. Attendees will learn about cutting-edge techniques for improving scholarly information re.
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Deep learning Preparation Course in Arabic Part 1 : Python

Embark on your machine learning journey with the Deep Learning Preparation Course in Arabic, Part 1: Python. Learn the essential skills needed to become a learning machine. This course is delivered by experts on Udemy, providing a comprehensive introduction to Python within the context of deep learning. Categories include: Python Courses.
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Machine Learning A-Z™: Hands-On Python & R in Data Science

Unlock the power of machine learning with the Machine Learning A-Z™ course, providing practical experience with Python and R. This Udemy course is designed for those looking to expand their knowledge in advanced data visualization, linear regression, decision trees, and essential libraries like NumPy and Pandas. Whether you're a budding data s.
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Python : Master Programming and Development with 15 Projects

Join our extensive Python course where you will delve into the complete Python programming landscape. This course offers a robust curriculum starting from the basics of Python and expanding into various fields such as Data Science, Data Visualization, Desktop Graphical Applications using Tkinter, and Machine Learning. With 15 hands-on project.
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Ensemble Machine Learning in Python: Random Forest, AdaBoost

Ensemble Machine Learning in Python: Random Forest, AdaBoost | Udemy Enhance your data science skills with our comprehensive course on ensemble machine learning in Python. Delve into powerful techniques like Random Forest and AdaBoost, as well as foundational ensemble methods such as Boosting, Bagging, and Bootstrap. This course is provided b.
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Machine Learning, Data Science and Generative AI with Python

Join our comprehensive, hands-on tutorial to delve into the realms of Machine Learning, Data Science, and Generative AI with Python. This course provides a deep dive into essential technologies and tools such as TensorFlow, GPT, OpenAI, and neural networks. Perfect for those seeking practical experience and aiming to advance their skills in m.
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More and more products are now being developed using artificial intelligence. To avoid being left on the sidelines of progress, managers must understand how the robot’s “brains” work

Artificial intelligence (AI) and machine learning technologies have been used for many years, but now the intensity of their use has increased significantly. For example, machine learning is being actively implemented in telecommunications, retail, marketing and e-commerce. But many still do not fully understand what it is.

Machine learning involves the system processing a large number of examples, during which it identifies patterns and uses them to predict the characteristics of new data. In other words, this is the process of giving AI ml courses “consciousness”, the ability to remember and analyze.

Machine learning use cases

The use of machine learning has touched many areas in our lives. Let's look at the most striking examples of the use of computer intelligence:

Facial recognition in the subway will help identify violators or criminals in a huge mass of people. Ordinary observers cannot cope with this task. But a fast-learning machine will do this job without any problems.

What do you need for machine learning (ML)?

For those interested in training, there are several requirements to be met in order to be successful in this field. So, there are the main points you need to know about the machine learning course. These requirements include:

  1. Basic knowledge of programming languages such as Python, R, Java, JavaScript, etc.

  2. Average knowledge of statistics and probability.

  3. Basic knowledge of linear algebra in the ml course. In a linear regression model, a line is drawn through all the data points, and that line is used to calculate new values.

  4. Understanding Calculus.

  5. Knowledge of how to clean and structure raw data into the desired format to reduce the time required for decision making.

Machine learning courses from AI Eeducation are the best choice!