Python: Master Machine Learning With Python: 3-In-1

你是一名数据科学家。每天，您都盯着大量数据，试图应用最新、最聪明的模型来发现新见解，但似乎存在无穷无尽的障碍。您的同事依靠您将公司的数据货币化 – 时间紧迫。你做什么？解决 Python 机器学习问题就是答案。机器学习让你对数据有强大的洞察力。如今，整个行业都采用了机器学习的实现，其概念很多。机器学习在现代数据驱动的世界中无处不在。用于搜索引擎、机器人、自动驾驶汽车等许多领域。机器学习与 Python 的有效结合，有助于实现现实世界问题的解决方案以及自动化分析模型。

这门全面的三合一课程是一个全面、实用的教程，可帮助您从不同场景的数据中获得精湛的洞察力，并轻松部署机器学习模型。通过这个基于项目的教程探索 Python 的强大功能并创建您自己的机器学习模型。尝试和测试解决常见问题的解决方案，同时使用 Python 实施机器学习。

内容和概述

该培训计划包括 3 门完整的课程，经过精心挑选，可为您提供最全面的培训。

第一门课程 Python 机器学习项目涵盖了机器学习与 Python 的富有洞察力的项目。该视频是一个独特的项目组合，可以教您什么是机器学习以及如何在实践中实施机器学习概念。六个不同的独立项目将帮助您掌握 Python 机器学习。该视频将涵盖分类、回归、聚类等概念，同时使用不同类型的数据库。完成本课程后，您将能够实施自己的机器学习模型。

第二门课程 Python 机器学习解决方案涵盖 100 个视频，教您如何在现实世界中执行各种机器学习任务。探索可以使用机器学习的一系列现实生活场景，并查看各种构建块。在整个课程中，您将使用各种机器学习算法来解决现实世界的问题，并使用 Python 来实现这些算法。发现如何处理各种类型的数据并探索机器学习范式（例如监督学习和非监督学习）之间的差异

第三门课程，Python 机器学习疑难解答，涵盖了您遇到的常见机器学习问题的实用且独特的解决方案。调试您的模型和研究管道，这样您就可以专注于提出新想法而不是修复旧错误。

在课程结束时，您将通过机器学习与 Python 的富有洞察力的项目一起运行，以在现实世界中执行各种机器学习任务。关于作者
Alexander T. Combs 是一位经验丰富的数据科学家、战略家和具有金融数据提取、自然语言处理和生成以及定量和统计建模背景的开发人员。他目前是纽约市数据科学沉浸式项目的全职首席讲师。

Prateek Joshi 是一位人工智能研究员，出版了五本书，还是 TEDx 演讲者。他是 Pluto AI 的创始人，这是一家由风险投资资助的硅谷初创公司，为深度学习提供支持的智能水管理分析平台。他在该领域的工作已在主要 IEEE 会议上获得专利、技术演示和研究论文。他曾受邀在包括 TEDx、AT&T Foundry、硅谷深度学习和开放硅谷在内的技术和创业会议上发表演讲。Prateek 还曾担任著名科技杂志的客座作者。他的科技博客在 200 多个国家/地区获得了超过 120 万的页面浏览量，并拥有 6,600 多名关注者。他经常就人工智能、Python 编程和抽象数学等主题撰写文章。他是一名狂热的编码员，并利用各种技术赢得了许多黑客马拉松比赛。他毕业于南加州大学，获得硕士学位，专攻人工智能。他曾在 Nvidia 和 Microsoft Research 等公司工作。Colibri 是一家技术咨询公司，由 James Cross 和 Ingrid Funie 于 2015 年创立。该公司致力于帮助其客户驾驭快速变化和复杂的新兴技术世界，在大数据、数据科学、机器学习和云计算等领域拥有深厚的专业知识。在过去的几年里，他们与一些世界上最大和最负盛名的公司合作，包括一家一级投资银行、一家领先的管理咨询集团，以及世界上最受欢迎的软饮料公司之一，帮助他们所有人更好地理解他们的数据，并以更智能的方式处理数据。该公司遵循其座右铭：数据 -> 智能 -> 行动。Rudy Lai 是 Quant Copy 的创始人，这是一家使用 AI 向潜在客户编写销售电子邮件的销售加速初创公司。通过从您的管道中获取线索，Quant Copy 在线研究它们并根据该数据生成销售电子邮件。它还具有一套电子邮件自动化工具来安排、发送和跟踪电子邮件性能——所有这些关键分析都反馈到我们的 AI 如何生成内容。在创立 Quant Copy 之前，Rudy 经营着一家机器学习咨询公司 HighDimension.IO，在那里他亲身经历了对外销售和潜在客户的挫折。作为创始合伙人，他通过 HighDimension.IO 的机器学习即服务帮助初创企业和企业，

在他职业生涯的第一部分，Rudy 在摩根士丹利等领先的投资银行从事量化交易工作超过 5 年。这段宝贵的经历让他见证了数据的力量，也见证了使用数据科学和机器学习实现自动化的陷阱。量化交易也是一个很好的平台，可以从中学习很多关于商业环境中的强化学习和监督学习主题。Rudy 拥有伦敦帝国理工学院的计算机科学学位，他是该校院长名单的一员，并获得过德意志银行人工智能奖等奖项。

Practical and unique solutions to common Machine Learning problems that you face!

What you’ll learn

Evaluate and apply the most effective models to problems
Deploy machine learning models using third-party APIs
Interact with text data and build models to analyze it
Use deep neural networks to build an optical character recognition system
Work with image data and build systems for image recognition and biometric face recognition
Eliminate common data wrangling problems in Pandas and scikit-learn as well as solve prediction visualization issues with Matplotlib
Explore data visualization techniques to interact with your data in diverse ways

Requirements

Prior familiarity with Python programming is assumed.
Basic understanding of Machine Learning concepts would certainly be useful.

Description

You are a data scientist. Every day, you stare at reams of data trying to apply the latest and brightest of models to uncover new insights, but there seems to be an endless supply of obstacles. Your colleagues depend on you to monetize your firm’s data – and the clock is ticking. What do you do?Troubleshooting Python Machine Learning is the answer.Machine learning gives you powerful insights into data. Today, implementations of machine learning are adopted throughout Industry and its concepts are many. Machine learning is pervasive in the modern data-driven world. Used across many fields such as search engines, robotics, self-driving cars, and more.The effective blend of Machine Learning with Python, helps in implementing solutions to real-world problems as well as automating analytical model.

This comprehensive 3-in-1 course is a comprehensive, practical tutorial that helps you get superb insights from your data in different scenarios and deploy machine learning models with ease. Explore the power of Python and create your own machine learning models with this project-based tutorial. Try and test solutions to solve common problems, while implementing Machine learning with Python.

Contents and Overview

This training program includes 3 complete courses, carefully chosen to give you the most comprehensive training possible.

The first course, Python Machine Learning Projects, covers Machine Learning with Python’s insightful projects. This video is a unique blend of projects that teach you what Machine Learning is all about and how you can implement machine learning concepts in practice. Six different independent projects will help you master machine learning in Python. The video will cover concepts such as classification, regression, clustering, and more, all the while working with different kinds of databases. You’ll be able to implement your own machine learning models after taking this course.

The second course, Python Machine Learning Solutions, covers 100 videos that teach you how to perform various machine learning tasks in the real world. Explore a range of real-life scenarios where machine learning can be used, and look at various building blocks. Throughout the course, you’ll use a wide variety of machine learning algorithms to solve real-world problems and use Python to implement these algorithms. Discover how to deal with various types of data and explore the differences between machine learning paradigms such as supervised and unsupervised learning

The third course, Troubleshooting Python Machine Learning, covers practical and unique solutions to common Machine Learning problems that you face. Debug your models and research pipelines, so you can focus on pitching new ideas and not fixing old bugs.

By the end of the course, you’ll get up-and-running via Machine Learning with Python’s insightful projects to perform various Machine Learning tasks in the real world.About the Authors
Alexander T. Combs is an experienced data scientist, strategist, and developer with a background in financial data extraction, natural language processing and generation, and quantitative and statistical modeling. He is currently a full-time lead instructor for a data science immersive program in New York City.

Prateek Joshi is an Artificial Intelligence researcher, the published author of five books, and a TEDx speaker. He is the founder of Pluto AI, a venture-funded Silicon Valley startup building an analytics platform for smart water management powered by deep learning. His work in this field has led to patents, tech demos, and research papers at major IEEE conferences. He has been an invited speaker at technology and entrepreneurship conferences including TEDx, AT&T Foundry, Silicon Valley Deep Learning, and Open Silicon Valley. Prateek has also been featured as a guest author in prominent tech magazines. His tech blog has received more than 1.2 million page views from over 200 countries and has over 6,600+ followers. He frequently writes on topics such as Artificial Intelligence, Python programming, and abstract mathematics. He is an avid coder and has won many hackathons utilizing a wide variety of technologies. He graduated from University of Southern California with a Master’s degree, specializing in Artificial Intelligence. He has worked at companies such as Nvidia and Microsoft Research.Colibriis 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 like 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 all of them to better make sense of their data, and process it in more intelligent ways. The company lives by its motto: Data -> Intelligence -> Action.Rudy Lai is the founder of Quant Copy, a sales acceleration startup using AI to write sales emails to prospects. By taking in leads from your pipelines, Quant Copy 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 generated content. Prior to founding Quant Copy, 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 a lot about reinforcement learning 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.