Edureka
Machine Learning and NLP Basics
Edureka

Machine Learning and NLP Basics

This course is part of Learn Generative AI with LLMs Specialization

Taught in English

Edureka

Instructor: Edureka

Included with Coursera Plus

Course

Gain insight into a topic and learn the fundamentals

Beginner level

Recommended experience

19 hours (approximately)
Flexible schedule
Learn at your own pace

What you'll learn

  • Master ML and deep learning, and apply NLP for advanced text analysis and classification.

Details to know

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Recently updated!

April 2024

Assessments

15 assignments

Course

Gain insight into a topic and learn the fundamentals

Beginner level

Recommended experience

19 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the Learn Generative AI with LLMs Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
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There are 4 modules in this course

This module of our course offers a comprehensive dive into the fundamentals, types, and applications of Machine Learning (ML), a pivotal aspect of artificial intelligence. It is meticulously crafted to transition learners from the basics of AI and predictive models in ML to a deeper understanding of different ML types—such as supervised, unsupervised, semi-supervised, and reinforcement learning. It further explores key concepts in classification and regression, including decision trees, random forests, and model optimization techniques. This module serves as both a foundational and an advanced exploration, catering to a broad spectrum of learners aiming to master machine learning.

What's included

28 videos4 readings4 assignments1 discussion prompt

This module provides a comprehensive exploration of deep neural networks, covering fundamental concepts, practical implementations, and advanced techniques. From understanding the basics of deep learning and its comparison with human brain functioning to delving into specific architectures like Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) with Long Short-Term Memory (LSTM), this module equips learners with the knowledge and skills needed to design, train, and optimize deep learning models for various tasks, including image classification and sequence prediction

What's included

70 videos9 readings6 assignments5 discussion prompts

This Module introduces the fundamentals of text mining and analysis. It covers various techniques for extracting, cleaning, and preprocessing text data, including tokenization, stemming, lemmatization, and named entity recognition. Additionally, the module explores methods for analyzing sentence structure, such as syntax trees and chunking, along with text classification techniques using bag-of-words, count vectorizers, and multinomial naive Bayes classifiers. Through practical assignments and discussions, learners gain insights into the applications of text mining across different domains and the essential tools and processes involved in working with textual data.

What's included

39 videos4 readings4 assignments3 discussion prompts

This module is the final stage of the course, offering learners a comprehensive review and evaluation of the knowledge and skills acquired throughout the modules. Throughout the module learners engage in various activities to solidify their learning and assess their understanding of the course material. These activities include completing a practice project that applies learned concepts to real-world scenarios, undertaking a graded assignment to evaluate proficiency, and potentially viewing a course completion video summarizing key takeaways and achievements.

What's included

1 video1 reading1 assignment

Instructor

Edureka
Edureka
38 Courses15,298 learners

Offered by

Edureka

Recommended if you're interested in Machine Learning

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