2024 Advanced Machine Learning and Deep Learning Projects

2024 Advanced Machine Learning and Deep Learning Projects, available at $49.99, has an average rating of 4.47, with 32 lectures, based on 102 reviews, and has 16472 subscribers.

You will learn about Advanced NLP for Data Scientists Advanced Image Processing Text Data Processing Text and Image Data Embeddings into the Same Vector Space Implement Image Search like Googles Image Search Cluster Text and Image Data This course is ideal for individuals who are Who have basic knowledge of ML or Who want to skill up or Who want to boost their career It is particularly useful for Who have basic knowledge of ML or Who want to skill up or Who want to boost their career.

Enroll now: 2024 Advanced Machine Learning and Deep Learning Projects

Summary

Title: 2024 Advanced Machine Learning and Deep Learning Projects

Price: $49.99

Average Rating: 4.47

Number of Lectures: 32

Number of Published Lectures: 32

Number of Curriculum Items: 32

Number of Published Curriculum Objects: 32

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Advanced NLP for Data Scientists

Advanced Image Processing

Text Data Processing

Text and Image Data Embeddings into the Same Vector Space

Implement Image Search like Googles Image Search

Cluster Text and Image Data

Who Should Attend

Who have basic knowledge of ML

Who want to skill up

Who want to boost their career

Target Audiences

Who have basic knowledge of ML

Who want to skill up

Who want to boost their career

This advanced machine learning and deep learning course will cover the following topics:

SBERT and BERT: These are pre-trained models that are used for natural language processing tasks such as sentence classification, named entity recognition, and question answering.

Sentence Embedding and Similarity Measures: Techniques for representing sentences as numerical vectors, and methods for comparing the similarity between sentences.

Clustering: Algorithms for grouping similar data points together, such as k-means and hierarchical clustering.

Text Summarization: Techniques for automatically generating a concise summary of a longer text.

Question Answering: Techniques for automatically answering questions based on a given text.

Image Clustering: Algorithms for grouping similar images together.

Image Search: Techniques for searching for images based on their content.

Throughout the course, students will work on hands-on projects that will help them apply the concepts they have learned to real-world problems. They will also get an opportunity to implement the latest state of the art techniques in the field to solve various NLP and CV problems.

By the end of this course, your confidence will boost in creating and analyzing the Image and Text Processing ML model in Python. You’ll have a thorough understanding of how to use Text Data and Image Data modeling to create predictive models and solve real-world business problems.

How this course will help you?

This course will give you a very solid foundation in machine learning. You will be able to use the concepts of this course in other machine learning models. If you are a business manager or an executive or a student who wants to learn and excel in machine learning, this is the perfect course for you.

What makes us qualified to teach you?

I am a Ph.D. Scholar in Machine Learning and taught tens of thousands of students over the years through my classes at the KGP Talkie YouTube channel. A few of my courses are part of Udemy’s top 5000 courses collection and curated for Udemy Business. I promise you will not regret it.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Download Code Files

Chapter 2: Natural Language Processing Projects

Lecture 1: SBERT Sentence Transformers Introduction

Lecture 2: SBERT Research Paper Review

Lecture 3: BERT Transformers Introduction

Lecture 4: Siamese Network in SBERT

Lecture 5: Project 1- Sentence Embeddings and Similarity Part 1

Lecture 6: Project 1- Sentence Embeddings and Similarity Part 2

Lecture 7: Project 2- Semantic Search Introduction

Lecture 8: Project 2- Semantic Search Coding

Lecture 9: Project 3- K-Mean Clustering on Text Data

Lecture 10: Project 3- Agglomerative Clustering on Text Data

Lecture 11: Project 3- Fast Clustering on Quora Questions Set

Lecture 12: Project 4- Build Quora Questions Auto-Complete Suggester – Part 1

Lecture 13: Project 4- Build Quora Questions Auto-Complete Suggester – Part 2

Lecture 14: Project 5- Similar Research Paper Recommendation System Part 1

Lecture 15: Project 5- Similar Research Paper Recommendation System Part 2

Lecture 16: Project 5- Similar Research Paper Recommendation System Part 3

Lecture 17: Project 6- Question Answer Retrieval System using NLP Part 1

Lecture 18: Project 6- Question Answer Retrieval System using NLP Part 2

Lecture 19: Project 6- Question Answer Retrieval System using NLP Part 3

Lecture 20: Project 7- Extractive Text Summarization Part 1

Lecture 21: Project 7- Extractive Text Summarization Part 2

Chapter 3: Image Processing Projects

Lecture 1: Project 1- Text to Image Search Introduction

Lecture 2: Project 1- Text to Image Search Coding Part 1

Lecture 3: Project 1- Text to Image Search Coding Part 2

Lecture 4: Project 2- Image Search from Hindi, Spanish, and French Text Data Part 1

Lecture 5: Project 2- Image Search from Hindi, Spanish, and French Text Data Part 2

Lecture 6: Project 3- Unsupervised Image Clustering Part 1

Lecture 7: Project 3- Unsupervised Image Clustering Part 2

Lecture 8: Project 3- Unsupervised Image Clustering Part 3

Lecture 9: Project 4- Finding Duplicated Images and Near Duplicates

Lecture 10: Project 5- Zero-Shot Image Classification

Instructors

Laxmi Kant | KGP Talkie
AVP, Data Science Join Ventures | IIT Kharagpur | KGPTalkie

Rating Distribution

1 stars: 2 votes

2 stars: 5 votes

3 stars: 10 votes

4 stars: 23 votes

5 stars: 62 votes

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