Applied Advanced Machine Learning In Python

学习应用数据科学和机器学习，通过 Udemy 上最现代、最新的数据科学课程（我们使用最新版本的 Python、Tensorflow 2.0 和其他库）获得工作并享受乐趣。本课程专注于效率：不再花时间在令人困惑、过时、不完整的机器学习教程上。我们非常有信心，这是您在任何地方都能找到的关于该主题的最全面、最现代的课程（我们知道，这是大胆的声明）。

这门基于项目的综合课程将向您介绍数据科学家的所有现代技能，并且在此过程中，我们将构建许多现实世界的项目以添加到您的投资组合中。您将可以访问所有代码、工作簿，以便您可以立即将它们放在您的作品集中！我们相信这门课程解决了进入数据科学和机器学习领域的最大挑战：在一个地方拥有所有必要的资源，并学习雇主想要的最新趋势和在职技能。

当我们从头到尾引导您成为一名专业的机器学习和数据科学工程师时，课程将非常实用。

本课程涵盖的主题是

让我们详细了解机器学习

在开始之前你需要知道的关于机器学习的一切

所有 ML 模型构建的一般方法

推进 ML 模型的概述

关于 Adv ML 模型的事实

梯度提升技术的基础知识

动手教程 – 使用 Python 的 GBM

AddaBoost 简介

AddaBoost 工作原理

使用 Python 进行 AddaBoost

XGBoost 概述，介绍

XGBoost 参数

XGBoost 与 Python-第 1 部分

XGBoost 与 Python-第 2 部分

XGBoost 与 Python-第 3 部分

XGBoost 结论

在本课程结束时，您将成为一名完整的数据科学家，可以被大公司聘用。我们将使用我们在课程中学到的一切来构建专业的现实世界项目。到最后，您将拥有一堆您已经构建的项目，您可以向其他人炫耀。

事实是这样的：大多数课程都会教你数据科学并做到这一点。他们向您展示如何开始。但问题是，你不知道从那里去哪里或如何构建自己的项目。或者他们在屏幕上向你展示了很多代码和复杂的数学，但它们并不能很好地解释事情，让你自己去解决现实生活中的机器学习问题。

无论您是编程新手，还是想提升您的数据科学技能，或者来自不同的行业，本课程都适合您。本课程不是让您在不了解原理的情况下编写代码，这样当您完成课程后，除了观看另一个教程之外，您不知道该做什么。不！本课程将推动您并挑战您从数据科学经验的初学者转变为可以推进模型构建的人。

机器学习在商业营销和金融、医疗保健、网络安全、零售、运输和物流、农业、物联网、游戏和娱乐、患者诊断、欺诈检测、制造业异常检测、政府、学术界/研究、推荐系统和那么多。在本课程中学到的技能将为您的职业生涯提供很多选择。

您会听到诸如人工神经网络或人工智能 (AI) 之类的陈述，并且在本课程结束时，您将最终理解这些陈述的含义！

MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz
Language: English | Size: 2.52 GB | Duration: 2h 56m

Advanced Machine Learning In Python Programming Language

What you’ll learn
Fundamentals about Machine Learning & how it is better than conventional automations
Starting From What Is Machine Learning To Practical Implementation
Covers Detailed Concept Of All ML Models & Algorithms-Basic To Adv
How To Build Your ML Models On Real Data Set
Fine tuning Of The Models For Better Accuracy & Prediction
Understanding The Parameters Of All Kinds Of ML Models
Steps Involved In ML Model Building & Important Terms
How To improve The Accuracy Using Advance Techniques .
Important Model Evaluation Metrics & Important Resources

Requirements
Student should have a fair idea about Python Programming Language and Google Colab IDE
Student should be familiar with the basic ML Model building and statistics behind that.
Description
Learn the hands-on tutorial on Advance Machine Learning Algorithms like GBM, AddaBoosting techniques, XGBoost, and many more.This Course Will Give You A Precise Approach To Machine Learning

Starting From What Is Machine Learning To Practical Implementation

Covers Detailed Concept Of All ML Models & Algorithms-Basic To Adv.

How To Build Your ML Models On Real Data Set.

Fine-tuning Of The Models For Better Accuracy & Prediction.

Understanding The Parameters Of All Kinds Of ML Models.

Steps Involved In ML Model Building & Important Terms.

Machine Learning In MS Excel, Python & R Prog. Lang.

Salary Structure And Role Of ML Practitioner.

How To Improve Accuracy Using Advance Techniques.

Important Model Evaluation Metrics & Important Resources

Learn the Applied Data Science and Machine Learning, get hired and have fun along the way with the most modern, up-to-date Data Science course on Udemy (we use the latest version of Python, Tensorflow 2.0 and other libraries). This course is focused on efficiency: never spend time on confusing, out of date, incomplete Machine Learning tutorials anymore. We are pretty confident that this is the most comprehensive and modern course you will find on the subject anywhere (bold statement, we know).

This comprehensive and project-based course will introduce you to all of the modern skills of a Data Scientist and along the way, we will build many real-world projects to add to your portfolio. You will get access to all the code, workbooks, so that you can put them on your portfolio right away! We believe this course solves the biggest challenge to entering the Data Science and Machine Learning field: having all the necessary resources in one place and learning the latest trends and on-the-job skills that employers want.

The curriculum is going to be very hands-on as we walk you from start to finish about becoming a professional Machine Learning and Data Science engineer.

The topics covered in this course are

Let’s Understand Machine Learning In Details

Everything You Need To Know About ML Before Getting Started

General Approach To All ML Model Building

Overview To Advance ML Models

Facts About Adv ML Models

Fundamentals About Gradient Boosting Technique

Hands On Tutorial- GBM With Python

Intro To AddaBoost

AddaBoost Working Principle

AddaBoost With Python

XGBoost Overview, Intro

XGBoost Parameters

XGBoost With Python-Part 1

XGBoost With Python-Part 2

XGBoost With Python-Part 3

XGBoost Conclusion

By the end of this course, you will be a complete Data Scientist that can get hired at large companies. We are going to use everything we learn in the course to build professional real world projects. By the end, you will have a stack of projects you have built that you can show off to others.

Here’s the truth: Most courses teach you Data Science and do just that. They show you how to get started. But the thing is, you don’t know where to go from there or how to build your own projects. Or they show you a lot of code and complex math on the screen, but they don’t really explain things well enough for you to go off on your own and solve real-life machine learning problems.

Whether you are new to programming, or want to level up your Data Science skills, or are coming from a different industry, this course is for you. This course is not about making you just code along without understanding the principles so that when you are done with the course you don’t know what to do other than watch another tutorial. No! This course will push you and challenge you to go from a beginner in Data Science experience to someone that can go off to advance model building.

Machine Learning has applications in Business Marketing and Finance, Healthcare, Cybersecurity, Retail, Transportation and Logistics, Agriculture, Internet of Things, Gaming and Entertainment, Patient Diagnosis, Fraud Detection, Anomaly Detection in Manufacturing, Government, Academia/Research, Recommendation Systems and so much more. The skills learned in this course are going to give you a lot of options for your career.

You hear statements like Artificial Neural Network, or Artificial Intelligence (AI), and by the end of this course, you will finally understand what these mean!

Who this course is for
Intermediate & Advance Machine Learning Enthusiasts