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所在平台: Udemy |
课程主页: https://www.udemy.com/course/practical-artificial-intelligence-ai-with-h2o-in-python/
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课程名称：使用 H2O 的实用人工智能（AI）与 Python 课程概述：本课程是 H2O 数据科学包的全面指南，专注于 Python 中的机器学习和深度学习。通过学习本课程，您将掌握强大的 Python 支持的数据科学框架，从而无需再参加其他课程或购买额外书籍。在大数据的时代，全球各地的公司都在利用 Python 从海量信息中提取有价值的信息。掌握基于 H2O 的机器学习、神经网络和深度学习技术，可以为您的公司提供竞争优势，同时也能推动您的职业发展。 授课教师介绍：课程由牛津大学地理与环境学硕士毕业生 Minerva Singh 主讲，拥有剑桥大学博士学位，专注于数据科学模型，具有超过 5 年的实际数据分析经验，并在国际同行评审期刊上发表过多篇论文。她注意到大多数 Python 数据科学课程和书籍未考虑主题的多维性，因此设计了本课程，以提供扎实的神经网络和深度学习的实际基础。 课程内容：您将在课程中从数据读取与清洗开始，最终实现强大的神经网络和深度学习算法，并评估其性能。课程将包括以下主题： - 介绍基于 Python 的强大深度学习包 H2O。 - 掌握机器学习的重要概念，避免冗长的术语。 - 使用 H2O 框架实现监督和无监督算法。 - 确定最重要的变量。 - 实现人工神经网络（ANN）和深度神经网络（DNN）。 无需先前的 Python 或统计/机器学习知识：课程从最基本的 Python 数据科学知识和技术开始，采用易于理解的实践方法，简化并解决最复杂的 Python 概念。与很多使用虚构数据的课程不同，本课程将使用真实数据，让学生能够在实际环境中实施 Python 数据科学。通过本课程，您将能够轻松使用 H2O 数据科学包在 Python 中实现新的深度学习技术，处理包括真实图像数据在内的实际数据，并学习如何进行预处理和建模。 加入本课程，获取所有代码和数据，踏上实用人工智能的学习之旅！
YOUR COMPLETE GUIDE TO H2O: POWERFUL PYTHON PACKAGE FOR MACHINE LEARNING, & DEEP LEARNING IN PYTHON This course covers the main aspects of the H2O package for data science in Python. If you take this course, you can do away with taking other courses or buying books on Python-based data science as you will have the keys to a very powerful Python supported data science framework. In this age of big data, companies across the globe use Python to sift through the avalanche of information at their disposal. By becoming proficient in machine learning, neural networks and deep learning via a powerful framework, H2O in Python, you can give your company a competitive edge and boost your career to the next level!LEARN FROM AN EXPERT DATA SCIENTIST:My name is Minerva Singh and I am an Oxford University MPhil (Geography and Environment), graduate. I finished a PhD at Cambridge University, UK, where I specialized in data science models. I have +5 years of experience in analyzing real-life data from different sources using data science-related techniques and producing publications for international peer-reviewed journals.Over the course of my research, I realized almost all the Python data science courses and books out there do not account for the multidimensional nature of the topic. This course will give you a robust grounding in the main aspects of practical neural networks and deep learning. Unlike other Python instructors, I dig deep into the data science features of Python and give you a one-of-a-kind grounding in data science.You will go all the way from carrying out data reading & cleaning to finally implementing powerful neural networks and deep learning algorithms and evaluating their performance using Python.Among other things:You will be introduced to powerful Python-based deep learning packages such as H2O. You will be introduced to important concepts of machine learning without the jargon. You will learn how to implement both supervised and unsupervised algorithms using the H2O frameworkIdentify the most important variables. Implement both Artificial Neural Networks (ANN) and Deep Neural Networks (DNNs) with the H2O frameworkWork with real data within the frameworkNO PRIOR PYTHON OR STATISTICS/MACHINE LEARNING KNOWLEDGE IS REQUIRED:You'll start by absorbing the most valuable Python Data Science basics and techniques. I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts in Python. My course will help you implement the methods using real data obtained from different sources. Many courses use made-up data that does not empower students to implement Python-based data science in real-life.After taking this course, you'll easily use the data science package H2O to implement novel deep learning techniques in Python. You will get your hands dirty with real-life data, including real-life imagery data which you will learn to pre-process and model You'll even understand the underlying concepts to understand what algorithms and methods are best suited for your data. We will also work with real data and you will have access to all the code and data used in the course. JOIN MY COURSE NOW!
