Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
22 Hour(s) 14 Minute(s)
Language
English
Taught by
Neuralearn Dot AI
Rating
Course Overview
Master and Deploy Sentiment analysis and machine translation solutions with Tensorflow and Hugggingface Transformers
Sentiment analysis and machine translation models are used by millions of people every single day. These deep learning models (most notably transformers) power different industries today.
With the creation of much more efficient deep learning models, from the early 2010s, we have seen a great improvement in the state of the art in the domains of sentiment analysis and machine translation.
In this course, we shall take you on an amazing journey in which you'll master different concepts with a step-by-step approach. We shall start by understanding how to process text in the context of natural language processing, then we would dive into building our own models and deploying them to the cloud while observing best practices.
We are going to be using Tensorflow 2 (the world's most popular library for deep learning, built by Google) and Huggingface
You will learn:
The Basics of Tensorflow (Tensors, Model building, training, and evaluation).
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 translation with RNNs, attention, transformers, and Huggingface Transformers (T5)
Model Deployment (Onnx format, Quantization, Fastapi, Heroku Cloud)
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!!!
Course Content
- 10 section(s)
- 79 lecture(s)
- Section 1 Introduction
- Section 2 Tensors and variables
- Section 3 [PRE-REQUISCITE] Building neural networks with tensorflow
- Section 4 Text Preprocessing for Sentiment Analysis
- Section 5 Sentiment Analysis with Recurrent neural networks
- Section 6 Sentiment Analysis with transfer learning
- Section 7 Neural Machine Translation with Recurrent Neural Networks
- Section 8 Neural Machine Translation with Attention
- Section 9 Neural Machine Translation with Transformers
- Section 10 Sentiment Analysis with Transformers
What You’ll Learn
- The Basics of Tensors and Variables with Tensorflow
- Linear Regression, Logistic Regression and Neural Networks built from scratch.
- Basics of Tensorflow and training neural networks with TensorFlow 2.
- Model deployment
- Conversion from tensorflow to Onnx Model
- Quantization Aware training
- Building API with Fastapi
- Deploying API to the Cloud
- 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
- Neural Machine Translation with T5 in Huggingface transformers
- Attention Networks
- Transformers from scratch
Skills covered in this course
Reviews
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MMichael Asheampong
if you're already comfortable with TensorFlow, this course is a goldmine for NLP applications. The deep dive into word embeddings, recurrent neural networks (RNNs), and LSTMs was exceptional. The instructor provided clear code examples and practical tips for tackling common NLP challenges with TensorFlow 2 and Huggingface
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SStanley Dave
I loved the project-oriented approach of this course. Building real NLP applications with TensorFlow 2, like a machine translator or a chatbot, made the learning process incredibly practical and rewarding. The course provided excellent starter code and clear guidance, allowing me to experiment and deepen my understanding.
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OOmen Stephania
I had a basic understanding of NLP but no experience with TensorFlow. The instructor did a wonderful job of explaining both concepts clearly and concisely. The hands-on projects, like sentiment analysis and machine translation, were engaging and really helped solidify my learning. Highly recommend for anyone wanting to dive into NLP with TensorFlow 2.
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GGunti spandan
Audio is with disturbance not clear..
