The Conference for Machine Learning Innovation

Workshop: Advancements in Natural Language Processing (NLP)

Workshop
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Register until October 20:
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Join the ML Revolution!
Register until October 20:
✓ Save up to $233
✓ Team discount
✓ Extra Specials for Freelancers
Register Now
Join the ML Revolution!
Register until November 03:

✓ Save up to €494
✓ 10% Team Discount✓ Special discount for freelancers
Register Now
Join the ML Revolution!
Register until November 03:

✓ Save up to €494
✓ 10% Team Discount✓ Special discount for freelancers
Register Now
Join the ML Revolution!
Until the Conference starts:
✓ Group discount
✓ Special discount for freelancers
Register Now
Join the ML Revolution!
Until the Conference starts:
✓ Group discount
✓ Special discount for freelancers
Register Now
Infos
Tuesday, November 22 2022
11:00 - 18:30
Room:
Workshop Stage 1
Booking note:
NLP Workshop
Infos
Booking note:
NLP Workshop

Extracting knowledge from text data has always been one of the most researched topics in machine learning, but only recently have we witnessed breakthroughs that put NLP in the spotlight. Much information is stored in unstructured data, like text, which is extremely important in many different fields, from finance to social media and e-commerce.

In this workshop, we will go through Natural Language Processing fundamentals, such as pre-processing techniques, embedding, and more. It will be followed by practical coding examples, in python, to teach how to apply the theory to real use cases.

The goal of this workshop is to provide the attendees all the basic tools and knowledge they need to solve real problems and understand the most recent and advanced NLP topics.

Lesson 1 Text Representation

Familiarize yourself with NLP fundamentals and text preprocessing, to prepare the data for our models. We will go through the main steps like removing stopwords, stemming, One-Hot Encoding, and more.

  • Exercise: Apply text preprocessing methods on a simple dataset.
  • Outcome: You will be able to apply to appropriate methodology to preprocess the text.

Lesson 2 Topic Modeling 

We will see what LDA is and how it can help extract information from documents. We will also try different clustering techniques and implement a Non-negative Matrix factorization.

  • Exercise: Apply topic modeling techniques on a simple text.
  • Outcome: You will be able to apply to extract the main information from documents using topic modeling techniques. 

Lesson 3 Text classification 

We will learn how it’s possible to represent text and how a classifier can use this representation. We will use TF-Idf and experiment with a couple of supervised learning models.

  • Exercise: Build an NLP pipeline to perform classification.​
  • Outcome: You will be able to solve a text classification problem end to end.

Lesson 4 Introduction to Deep Learning in NLP

Understand word embedding, how it works and how to use it. We will go through the main concepts behind word embedding and see some practical examples using the Gensim library.

  • Exercise: Leveraging python deep learning libraries to create an NLP pipeline for sentiment analysis.​
  • Outcome: You will be able to use word embedding to perform any text classification task.

Lesson 5 Sequential Models

We will quickly introduce the most recent development of Deep learning in NLP, in particular we will see how to leverage BERT and ELMo and their pre-trained models to solve NLP problems.

  • Outcome: you will be able to understand the theory behind Sequential models and apply it to practical problems.

Lesson 6 Generative models

In this part we will see some technique to generate and summarize text. We will explore methods like Variational AutoEncoders (VAE) and Generative Adversarial Networks (GAN) and of course the most famous of them all, the GPT models from OpenAI. We will also see how to generate text using python.

  • Outcome: You will have a good understanding of generative models and how to use them to generate text in python.

This course is designed for data scientists, data analysts and software engineers who want to start working with NLP without treating it like a black box. They want to have an understanding of the theory but most importantly how to approach a real problem.

We will be using python in all exercises therefore some python knowledge is required. Some machine learning knowledge is beneficial but not required.

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This Session belongs to the Diese Session gehört zum Programm vom SingaporeSingapore and  und MunichMunich program. Take me to the program of . Hier geht es zum Programm von Berlin Berlin .

Take me to the full program of Zum vollständigen Programm von Munich Munich .

This Session Diese Session belongs to the gehört zum Programm von SingaporeSingapore and  und MunichMunich program. Take me to the current program of . Hier geht es zum aktuellen Programm von Singapore Singapore , Berlin Berlin or oder Munich Munich .

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