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所在平台: Udemy |
课程主页: https://www.udemy.com/course/hands-on-machine-learning-with-scikit-learn-and-tensorflow-2/
课程评论：没有评论
课程名称：用 Scikit-learn 和 TensorFlow 2 进行实践机器学习 课程概述：您是否在寻找一门教授有效机器学习方法的课程，专注于 Scikit-learn 和 TensorFlow 2.0？或者您一直希望掌握解决那些无法通过明确编程来处理的问题的高效技能？如果您已经熟悉 pandas 和 NumPy，本课程将为您提供最新、详细的实用机器学习方法知识，帮助您应对大多数不能轻易明确编程的任务。课程将展示学习算法，通过数据进行预测和决策。 理论部分将通过大量实际案例和 Jupyter Notebooks 中的代码示例进行支撑，旨在使您高效构建出在指定任务中可以达到最高准确率的算法和模型。完成课程后，您将能够自信地解决一系列基于行业的机器学习问题，通过训练、优化和将模型部署到生产环境中来实现有效预测和决策（例如，创建一个读取标记手写数字数据集的算法）。 作者简介：Samuel Holt 拥有多年为大型企业和初创公司实施、创建并投入生产的机器学习模型的经验，同时也是一名机器学习顾问。他拥有机器学习实验室经验，并获得牛津大学机器学习和软件工程的硕士学位，在学术上获得四个优秀奖项。他曾构建过使用 Scikit-learn 和 TensorFlow 的生产系统，包括自动客户支持、文档 OCR、自动驾驶汽车中的车辆检测、评论分析以及金融数据的时间序列预测。
Have you been looking for a course that teaches you effective machine learning in scikit-learn and TensorFlow 2.0? Or have you always wanted an efficient and skilled working knowledge of how to solve problems that can't be explicitly programmed through the latest machine learning techniques?If you're familiar with pandas and NumPy, this course will give you up-to-date and detailed knowledge of all practical machine learning methods, which you can use to tackle most tasks that cannot easily be explicitly programmed; you'll also be able to use algorithms that learn and make predictions or decisions based on data.The theory will be underpinned with plenty of practical examples, and code example walk-throughs in Jupyter notebooks. The course aims to make you highly efficient at constructing algorithms and models that perform with the highest possible accuracy based on the success output or hypothesis you've defined for a given task.By the end of this course, you will be able to comfortably solve an array of industry-based machine learning problems by training, optimizing, and deploying models into production. Being able to do this effectively will allow you to create successful prediction and decisions for the task in hand (for example, creating an algorithm to read a labeled dataset of handwritten digits).About the AuthorSamuel Holt has several years' experience implementing, creating, and putting into production machine learning models for large blue-chip companies and small startups (as well as within his own companies) as a machine learning consultant.He has machine learning lab experience and holds an MEng in Machine Learning and Software Engineering from Oxford University, where he won four awards for academic excellence.Specifically, he has built systems that run in production using a combination of scikit-learn and TensorFlow involving automated customer support, implementing document OCR, detecting vehicles in the case of self-driving cars, comment analysis, and time series forecasting for financial data.
