Deep Learning: Natural Language Processing with Transformers
What you'll learn
- The Basics of Tensors and Variables with Tensorflow
- Mastery of the fundamentals of Machine Learning and The Machine Learning Developmment Lifecycle.
- Basics of Tensorflow and training neural networks with TensorFlow 2.
- Sentiment Analysis with Recurrent neural networks, Attention Models and Transformers from scratch
- Neural Machine Translation with Recurrent neural networks, Attention Models and Transformers from scratch
- Recurrent Neural Networks, Modern RNNs, training sentiment analysis models with TensorFlow 2.
- Intent Classification with Deberta in Huggingface transformers
- Conversion from tensorflow to Onnx Model
- Building API with Fastapi
- Deploying API to the Cloud
- 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
- Basic Math
- No Programming experience.
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 There’s so much information out there, much of which is outdated and many times don't take the beginners into consideration :(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.
Who this course is for:
- Python Developers curious about Deep Learning for NLP
- Deep Learning Practitioners who want gain a mastery of how things work under the hoods
- Anyone who wants to master deep learning fundamentals and also practice deep learning for NLP using best practices in TensorFlow.
- Natural Language Processing practitioners who want to learn how state of art NLP models are built and trained using deep learning.
- Anyone wanting to deploy ML Models
- Learners who want a practical approach to Deep learning for Natural Language Processing
We provide world class courses in Mathematics for Deep Learning (Linear Algebra, Calculus, Probability, Statistics, Optimization), Core Deep Learning Theory (Going from the basics of Machine Learning up to most recent state of art Deep Learning Algorithms) and Practical Deep Learning applied in fields like Computer vision and Natural Language Processing, using modern tools like TensorFlow, PyTorch, HuggingFace, KubeFlow, …