Intro to Natural Language Processing in Python for AI

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365 Careers,Lauren Newbould

2:52:10

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1 - Introduction

1 - Introduction to the course.mp4

02:39

2 - Introduction to NLP.mp4

01:36

3 - NLP in everyday life.mp4

01:14

4 - Supervised vs Unsupervised NLP.mp4

01:46

2 - Text Preprocessing

5 - The importance of data preparation.mp4

01:45

6 - Lowercase.mp4

02:10

7 - Removing stop words.mp4

03:52

8 - Regular expressions.mp4

09:55

9 - Tokenization.mp4

02:51

10 - Stemming.mp4

02:45

11 - Lemmatization.mp4

02:21

12 - Ngrams.mp4

03:59

13 - Practical task.mp4

10:15

13 - tripadvisor-hotel-reviews.csv

3 - Identifying Parts of Speech and Named Entities

14 - Text tagging.mp4

01:24

15 - Parts of speech POS tagging.mp4

04:19

16 - Named entity recognition NER.mp4

03:44

17 - Practical task.mp4

08:56

17 - bbc-news.csv

4 - Sentiment Analysis

18 - What is sentiment analysis.mp4

01:59

19 - Rulebased sentiment analysis.mp4

05:24

20 - Pretrained transformer models.mp4

04:02

21 - Practical task.mp4

05:42

21 - book-reviews-sample.csv

5 - Vectorizing Text

22 - Numerical representation of text.mp4

01:39

23 - Bag of Words model.mp4

03:03

24 - TFIDF.mp4

03:36

6 - Topic Modelling

25 - What is topic modelling.mp4

02:56

26 - When to use topic modelling.mp4

01:33

27 - Latent Dirichlet Allocation.mp4

02:19

28 - LDA in Python.mp4

04:25

28 - news-articles.csv

29 - Latent Semantic Analysis.mp4

01:39

30 - LSA in Python.mp4

01:21

7 - Builing Your Own Text Classifier

31 - Building a custom text classifier.mp4

00:56

32 - Logistic regression.mp4

04:40

33 - Naive Bayes.mp4

01:33

34 - Linear Support Vector Machine.mp4

02:24

8 - Case Study Categorizing Fake News

35 - Introducing the project.mp4

03:32

35 - fake-news-data.csv

36 - Exploring our data through POS tags.mp4

09:24

37 - Extracting named entities.mp4

04:51

38 - Processing the text.mp4

08:14

39 - Does sentiment differ between news types.mp4

05:11

40 - What topics appear in fake news Part 1.mp4

06:11

41 - What topics appear in fake news Part 2.mp4

05:56

42 - Categorizing fake news with a custom classifier.mp4

05:48

9 - The Future of NLP

43 - What is deep learning.mp4

03:04

44 - Deep learning for NLP.mp4

01:51

45 - NonEnglish NLP.mp4

01:48

46 - Whats next for NLP.mp4

01:38

Description

Learn the Technology Behind AI Tools Like ChatGPT: Understanding, Generating, and Classifying Human Language

What You'll Learn?

Natural Language Processing for AI
Text preprocessing techniques
Text tagging and entity extraction
Sentiment analysis
Uncovering topics in the text
Text classification
Vectorizing text for machine learning

Who is this for?

Aspiring data scientists and AI engineers

AI and LLM students

Data science students

Data scientists

Anyone interested to learn how to work with Natural Language Processing

What You Need to Know?

Basic Python programming skills

More details

Description
Are you passionate about Artificial Intelligence and Natural Language Processing?
Do you want to pursue a career as a data scientist or as an AI engineer?
If thatâ€™s the case, then this is the perfect course for you!
In this Intro to Natural Language Processing in Python course you will explore essential topics for working with text data. Whether you want to create custom text classifiers, analyze sentiment, or explore concealed topics, youâ€™ll learn how NLP works and obtain the tools and concepts necessary to tackle these challenges.
Natural language processing is an exciting and rapidly evolving field that fundamentally impacts how we interact with technology. In this course, youâ€™ll learn to unlock the power of natural language processing and will be equipped with the knowledge and skills to start working on your own NLP projects.
The training offers you access to high quality Full HD videos and practical coding exercises. This is a format that facilitates easy comprehension and interactive learning. One of the biggest advantages of all trainings produced by 365 Data Science is their structure. This course makes no exception. The well-organized curriculum ensures you will have an amazing experience.
You wonâ€™t need prior natural language processing training to get startedâ€”just basic Python skills and familiarity with machine learning.
This introduction to NLP guides you step-by-step through the entire process of completing a project. Weâ€™ll cover models and analysis and the fundamentals, such as processing and cleaning text data and how to get data in the correct format for NLP with machine learning.
We'll utilize algorithms like Latent Dirichlet Allocation, Transformer models, Logistic Regression, Naive Bayes, and Linear SVM, along with such techniques as part-of-speech (POS) tagging and Named Entity Recognition (NER).
You'll get the opportunity to apply your newly acquired skills through a comprehensive case study, where we'll guide you through the entire project, covering the following stages:
Text cleansing
In-depth content analysis
Sentiment analysis
Uncovering hidden themes
Ultimately crafting a customized text classification model
By completing the course, youâ€™ll receive Ð° verifiable NLP certificate and will add an excellent project to your portfolio to show off your ability to analyze text like a pro.
So, what are you waiting for?
Click Buy Now and start your AI journey today!
Who this course is for:
Aspiring data scientists and AI engineers
AI and LLM students
Data science students
Data scientists
Anyone interested to learn how to work with Natural Language Processing

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365 Careers is the #1 best-selling provider of business, finance, and data science courses on Udemy. The company’s courses have been taken by more than 2,000,000 students in 210 countries. People working at world-class firms like Apple, PayPal, and Citibank have completed 365 Careers trainings. Currently, 365 focuses on the following topics on Udemy: 1) Finance – Finance fundamentals, Financial modeling in Excel, Valuation, Accounting, Capital budgeting, Financial statement analysis (FSA), Investment banking (IB), Leveraged buyout (LBO), Financial planning and analysis (FP&A), Corporate budgeting, applying Python for Finance, Tesla valuation case study, CFA, ACCA, and CPA2) Data science – Statistics, Mathematics, Probability, SQL, Python programming, Python for Finance, Business Intelligence, R, Machine Learning, TensorFlow, Tableau, the integration of SQL and Tableau, the integration of SQL, Python, Tableau, Power BI, Credit Risk Modeling, and Credit Analytics, Data literacy, Product Management, Pandas, Numpy, Python Programming, Data Strategy3) Entrepreneurship – Business Strategy, Management and HR Management, Marketing, Decision Making, Negotiation, and Persuasion, Tesla's Strategy and Marketing4) Office productivity – Microsoft Excel, PowerPoint, Microsoft Word, and Microsoft Outlook5) Blockchain for BusinessAll of our courses are: - Pre-scripted - Hands-on - Laser-focused - Engaging - Real-life tested By choosing 365 Careers, you make sure you will learn from proven experts, who have a passion for teaching, and can take you from beginner to pro in the shortest possible amount of time. If you want to become a financial analyst, a data scientist, a business analyst, a data analyst, a business intelligence analyst, a business executive, a finance manager, an FP&A analyst, an investment banker, or an entrepreneur365 Careers’ courses are the perfect place to start.

Lauren Newbould

Instructor's Courses

Guided by a comprehensive background in social science and statistics, Lauren's career has taken her through several pivotal roles; from creating custom NLP solutions for non-profits in Nepal, to providing insights for BBC Sport and the 2020 Olympics. Lauren has spoken at several conferences on how NLP can be used to benefit those in developing countries and is an advocate for ethical and open data science. Her aim is to empower individuals and organizations to make confident, data-driven decisions and make AI fair and accessible for all.

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