Deep Learning is a hot topic today! This is because of the impact it's having in several industries. One of the fields in which deep learning has the most influence today is Natural Language Processing.

To understand why Deep Learning based Natural Language Processing is so popular; it suffices to take a look at the different domains where giving a computer the power to understand and make sense out of text and generate text has changed our lives.

Some applications of Natural Language Processing are in:

• Helping people around the world learn about any topic ChatGPT

• Helping developers code more efficiently with Github Copilot.

• Automatic topic recommendation in our Twitter feeds

• Automatic Neural Machine Translation with  Google Translate

• E-commerce search engines like those of Amazon

• Correction of Grammar with Grammarly

The demand for Natural Language Processing engineers is skyrocketing and experts in this field are highly paid, because of their value. However, getting started in this field isn’t easy. There’s so much information out there, much of which is outdated and many times don't take the beginners into consideration :(

In this course, we shall take you on an amazing journey in which you'll master different concepts with a step-by-step and project-based approach. You shall be using Tensorflow 2 (the world's most popular library for deep learning, built by Google) and Huggingface transformers (most popular NLP focused library ). We shall start by understanding how to build very simple models (like Linear regression model for car price prediction and RNN text classifiers for movie review analysis) using Tensorflow to much more advanced transformer models (like Bert, GPT, BlenderBot, T5, Sentence Transformers and Deberta).

After going through this course and carrying out the different projects, you will develop the skill sets needed to develop modern deep learning for NLP solutions that big tech companies encounter.

You will learn: 

• The Basics of Tensorflow (Tensors, Model building, training, and evaluation)

• Text Preprocessing for Natural Language Processing.

• Deep Learning algorithms like Recurrent Neural Networks, Attention Models, Transformers, and Convolutional neural networks.

• Sentiment analysis with RNNs, Transformers, and Huggingface Transformers (Deberta)

• Transfer learning with Word2vec and modern Transformers (GPT, Bert, ULmfit, Deberta, T5...)

• Machine Learning Operations (MLOps) with Weights and Biases (Experiment Tracking, Hyperparameter Tuning, Dataset Versioning, Model Versioning)

• Machine translation with RNNs, attention, transformers, and Huggingface Transformers (T5)

• Model Deployment (Onnx format, Quantization, Fastapi, Heroku Cloud)

• Intent Classification with Deberta in Huggingface transformers

• Named Entity Relation with Roberta in Huggingface transformers

• Neural Machine Translation with T5 in Huggingface transformers

• Extractive Question Answering with Longformer in Huggingface transformers

• E-commerce search engine with Sentence transformers

• Lyrics Generator with GPT2 in Huggingface transformers

• Grammatical Error Correction with T5 in Huggingface transformers

• Elon Musk Bot with BlenderBot in Huggingface transformers

• Speech recognition with RNNs

  
  

If you are willing to move a step further in your career, this course is destined for you and we are super excited to help achieve your goals!

This course is offered to you by Neuralearn. And just like every other course by Neuralearn, we lay much emphasis on feedback. Your reviews and questions in the forum will help us better this course. Feel free to ask as many questions as possible on the forum. We do our very best to reply in the shortest possible time.

Enjoy!!!