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Advanced Machine Learning, Neural Networks, and NLP

Advanced Machine Learning, Neural Networks, and NLP

本课程是 CompTIA DataX Study Guide 专项课程的一部分

位教师：Wiley Skills Network

包含在中

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4个模块

深入了解一个主题并学习基础知识。

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推荐体验

5 小时完成

灵活的计划

自行安排学习进度

4个模块

深入了解一个主题并学习基础知识。

高级设置等级

推荐体验

5 小时完成

灵活的计划

自行安排学习进度

您将学到什么

Master advanced supervised machine learning techniques such as regression, decision trees, and ensemble methods.
Understand neural network architectures and deep learning techniques for complex problem-solving.
Explore NLP techniques like tokenization, sentiment analysis, and word embeddings for text data processing.

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Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

积累特定领域的专业知识

本课程是 CompTIA DataX Study Guide 专项课程专项课程的一部分

在注册此课程时，您还会同时注册此专项课程。

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该课程共有4个模块

This course explores advanced machine learning techniques, neural networks, and natural language processing (NLP), all of which are critical in today’s data-driven world. Mastery of these skills enables professionals to solve complex problems in areas such as AI, automation, and big data analytics.

By diving deep into supervised learning, neural networks, and NLP, learners will enhance their ability to create sophisticated models and systems capable of handling large-scale, unstructured data. These skills are highly valued in industries like finance, healthcare, and technology. What makes this course unique is its balance between theoretical knowledge and practical, hands-on application. You will not only grasp the underlying algorithms but also learn how to implement them in real-world projects, enhancing your ability to apply machine learning and NLP to solve real challenges. This course is ideal for data scientists, machine learning engineers, and AI researchers looking to expand their expertise. A background in basic machine learning concepts and programming is recommended for the best experience. This course is part three of a three-course Specialization designed to provide a comprehensive learning pathway in this subject area. While it delivers standalone value and practical skills, learners seeking a more integrated and in-depth progression may benefit from completing the full Specialization. From CompTIA DataX Study Guide Copyright © 2024 by John Wiley & Sons, Inc. All rights, including for text and data mining, AI training, and similar technologies, are reserved. Used by arrangement with John Wiley & Sons, Inc.

单元详情

In this section, we examine key supervised machine learning techniques including linear and logistic regression, decision trees, and ensemble methods, while highlighting model assumptions, regularization, and real-world data science applications.

涵盖的内容

1个视频7篇阅读材料1个作业

In this section, we examine the architecture and core components of artificial neural networks, review deep learning techniques like dropout and batch normalization, and distinguish major deep learning architectures with practical use cases.

涵盖的内容

1个视频6篇阅读材料1个作业

1个视频总计1分钟

Neural Networks and Deep Learning - Overview Video1分钟

6篇阅读材料总计65分钟

Introduction10分钟
Threshold Activation Function15分钟
Batch Normalization10分钟
One-Shot, Zero-Shot, and Few-Shot Learning10分钟
Generative Adversarial Networks10分钟
Exam Essentials10分钟

1个作业总计10分钟

Neural Networks and Deep Learning Fundamentals10分钟

In this section, we explore key NLP techniques, covering text preparation (tokenization, stemming), text analysis (keyword extraction, sentiment analysis), and text representation (vector space models, word embeddings) for practical language processing applications.

涵盖的内容

1个视频6篇阅读材料1个作业

In this section, we compare optimization models by exploring decision variables and constraints, and explain computer vision concepts with hands-on steps for image preprocessing and feature extraction in practical applications.