intermediate

Introduction to Natural Language Processing

Artificial Intelligence

Verified skills you'll gain

DEVELOPING

Feature Engineering and Text Representation

DEVELOPING

Machine Learning Modeling for NLP

DEVELOPING

Text Data Collection and Preparation

Tools you'll use

MatPlotLib

Pandas

Python

Scikit-learn

Seaborn

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This learning path offers foundational knowledge in Natural Language Processing (NLP). It covers data exploration, preprocessing, text vectorization, and machine learning for text classification. Gain proficiency in transforming text into insights and implementing models to classify text.

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1,086 learners

This introductory course guides you through the initial yet critical steps of any data science project: data exploration. By utilizing Python and specifically pandas, you'll learn to load, inspect, and analyze datasets to gain fundamental insights. These steps are crucial for preparing you for Natural Language Processing explorations.

Course 2

Text Data Preprocessing in Python

5 lessons

21 practices

Learn to clean and prepare textual data for machine learning models using Python. This course teaches you to apply basic preprocessing tasks such as text lowercasing, removing stopwords, tokenization, and stemming on the SMS Spam Collection dataset. By the end of this course, you’ll have the skills to transform raw text into a format that's ready for NLP tasks.

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Course 3

Introduction to TF-IDF Vectorization in Python

4 lessons

19 practices

Venture into the world of text vectorization with a focus on TF-IDF (Term Frequency-Inverse Document Frequency) in Python. Through this course, you'll learn how to convert text into numerical features that machine learning models can work with. Using the SMS Spam Collection dataset, you will understand how to apply TF-IDF to prepare text data for predictive modeling.

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Course 4

Building and Evaluating Text Classifiers in Python

5 lessons

20 practices

Progress from preprocessing text data to building predictive models with this practical course. You'll learn how to leverage machine learning algorithms, such as Naive Bayes and logistic regression, to classify text into categories. Using the preprocessed SMS Spam Collection dataset, the course guides you through training classifiers, making predictions, and evaluating their performance.

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Francisco Aguilar Meléndez

Data Scientist

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From our community

Hear what our customers have to say about CodeSignal Learn

I'm impressed by the quality and can't stop recommending it. It's also a lot of fun!

Francisco Aguilar Meléndez

Data Scientist

+11

I love that it's personalized. When I'm stuck, I don't have to hope my Google searches come out successful. The AI mentor Cosmo knows exactly what I need.

Faith Yim

Software Engineer

+14

It's an amazing product and exceeded my expectations, helping me prepare for my job interviews. Hands-on learning requires you to actually know what you are doing.

Alex Bush

Full Stack Engineer

I'm really impressed by the AI tutor Cosmo's feedback about my code. It's honestly kind of insane to me that it's so targeted and specific.

Abbey Helterbran

Tech consultant

I tried Leetcode but it was too disorganized. CodeSignal covers all the topics I'm interested in and is way more structured.

Jonathan Miller

Senior Machine Learning Engineer

+12

I'm impressed by the quality and can't stop recommending it. It's also a lot of fun!

Francisco Aguilar Meléndez

Data Scientist

+11

Introduction to Natural Language Processing

Verified skills you'll gain

Trusted by learners working at top companies

Turn screen time into skills time

Join the 1M+ learners on CodeSignal

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