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所在平台: Udemy |
课程主页: https://www.udemy.com/course/python-build-machine-learning-models-in-6-hours/
课程评论：没有评论
课程名称：Python：在6小时内构建机器学习模型 课程概述：随着数据量的不断增加，程序员和数据科学家必须提出更好的解决方案，以提高机器的智能化水平，减少人工工作，并找到解决日常任务中面临的障碍的方法。Python为构建更好的解决方案并高效处理数据提供了支持。本课程是一个综合性的2合1课程，教授您如何执行不同的机器学习任务，以及解决日常工作中常见的机器学习问题。您将学习如何使用标记数据集来分类对象或预测未来的数值，以提供更准确和有价值的分析。同时，您将使用未标记数据集进行分段和聚类，将大型数据集划分为合理的组。为了全面掌握这一技术，您还将学习使用Python构建预测模型的工具。 该培训项目包括两个完整的课程，精心选择以提供尽可能全面的培训。在第一个课程《用Python入门机器学习》中，您将学习如何使用标记数据集来分类对象或预测未来值，并了解如何清理数据及识别您面临的机器学习任务。第二个课程《使用机器学习和Python构建预测模型》将介绍您可以用Python构建预测模型的工具，课程通过一些有趣的实例，带您解决各种挑战，比如预测波士顿的房价、一个棒球选手的击球率、他们在泰坦尼克号上的生存几率等问题。 通过本课程，您将能够利用Python机器学习工具包，将其应用于自己的项目，只需少量代码便可构建和部署机器学习模型。 讲师介绍：该课程由Colibri Digital和Rudy Lai主讲。Colibri Digital是一家成立于2015年的技术咨询公司，专注于大数据、数据科学、机器学习和云计算等领域，为客户提供解决方案。Rudy Lai是销售加速初创公司QuantCopy的创始人，利用人工智能生成销售邮件。他在金融和机器学习领域具有丰富的经验，并在多个知名公司中担任过重要职务。 综上所述，此课程为希望在机器学习领域建立扎实基础的学习者提供了重要的知识和实用技能。
Given the constantly increasing amounts of data they're faced with, programmers and data scientists have to come up with better solutions to make machines smarter and reduce manual work along with finding solutions to the obstacles faced in between. Python comes to the rescue to craft better solutions and process them effectively.This comprehensive 2-in-1 course teaches you how to perform different machine learning tasks along with fixing common machine learning problems you face in your day-to-day tasks. You will learn how to use labeled datasets to classify objects or predict future values, so that you can provide more accurate and valuable analysis. You will also use unlabelled datasets to do segmentation and clustering, so that you can separate a large dataset into sensible groups. Further to get a complete hold on the technology, you will work with tools using which you can build predictive models in Python.This training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.In the first course, Getting Started with Machine Learning in Python, you will learn how to use labeled datasets to classify objects or predict future values, so that you can provide more accurate and valuable analysis. You will then use unlabelled datasets to do segmentation and clustering, so that you can separate a large dataset into sensible groups. You will also learn to understand and estimate the value of your dataset. Next, you will learn how to clean data for your application, and how to recognize which machine learning task you are dealing with.The second course, Building Predictive Models with Machine Learning and Python, will introduce you to tools with which you can build predictive models with Python, the core of a Data Scientist's toolkit. Through some really interesting examples, the course will take you through a variety of challenges: predicting the value of a house in Boston, the batting average of a baseball player, their survival chances had they been on the Titanic, or any other number of other interesting problems.By the end of this course, you will be able to take the Python machine learning toolkit and apply it to your own projects to build and deploy machine learning models in just a few lines of code. Meet Your Expert(s):We have the best work of the following esteemed author(s) to ensure that your learning journey is smooth:Colibri Digital is a technology consultancy company founded in 2015 by James Cross and Ingrid Funie. The company works to help its clients navigate the rapidly changing and complex world of emerging technologies, with deep expertise in areas such as big data, data science, Machine Learning, and cloud computing. Over the past few years, they have worked with some of the world's largest and most prestigious companies, including a tier 1 investment bank, a leading management consultancy group, and one of the world's most popular soft drinks companies, helping each of them to make better sense of its data, and process it in more intelligent ways. The company lives by its motto: Data -> Intelligence -> Action.Rudy Lai is the founder of QuantCopy, a sales acceleration startup using AI to write sales emails to prospects. By taking in leads from your pipelines, QuantCopy researches them online and generates sales emails from that data. It also has a suite of email automation tools to schedule, send, and track email performance-key analytics that all feed-back into how our AI generates content. Prior to founding QuantCopy, Rudy ran HighDimension.IO, a Machine Learning consultancy, where he experienced firsthand the frustrations of outbound sales and prospecting. As a founding partner, he helped startups and enterprises with HighDimension.IO's Machine-Learning-as-a-Service, allowing them to scale up data expertise in the blink of an eye. In the first part of his career, Rudy spent 5+ years in quantitative trading at leading investment banks such as Morgan Stanley. This valuable experience allowed him to witness the power of data, but also the pitfalls of automation using data science and Machine Learning. Quantitative trading was also a great platform from which to learn about reinforcement learning in depth, and supervised learning topics in a commercial setting. Rudy holds a Computer Science degree from Imperial College London, where he was part of the Dean's List, and received awards such as the Deutsche Bank Artificial Intelligence prize.
