- Welcome
- Introduction
- DO NOT SKIP IT | Download Working Files!!!
- What is BERT
- What is ktrain
- Going Deep Inside ktrain Package
- Notebook Setup
- Must Read This!!!
- Installing ktrain
- Loading Dataset
- Train-Test Split and Preprocess with BERT
- BERT Model Training
- Testing Fine Tuned BERT Model
- Saving and Loading Fine Tuned Model
Online
₹ 449 799
Quick facts
particular | details | |
---|---|---|
Medium of instructions
English
|
Mode of learning
Self study
|
Mode of Delivery
Video and Text Based
|
Course and certificate fees
Fees information
₹ 449 ₹799
certificate availability
Yes
certificate providing authority
Udemy
The syllabus
BERT | Sentiment Prediction | Multi Class Prediction Problem
Fine Tuning BERT for Disaster Tweets Classification
- Resources Folder
- BERT Intro - Disaster Tweets Dataset Understanding
- Download Dataset
- Target Class Distribution
- Number of Characters Distribution in Tweets
- Number of Words, Average Words Length, and Stop words Distribution in Tweets
- Most and Least Common Words
- One-Shot Data Cleaning
- Disaster Words Visualization with Word Cloud
- Classification with TFIDF and SVM
- Classification with Word2Vec and SVM
- Word Embeddings and Classification with Deep Learning Part 1
- Word Embeddings and Classification with Deep Learning Part 2
- BERT Model Building and Training
- BERT Model Evaluation
DistilBERT | Faster and Cheaper BERT model from Hugging Face
- What is DistilBERT?
- Notebook Setup
- Data Preparation
- DistilBERT Model Training
- Save Model at Google Drive
- Model Evaluation
- Download Fine Tuned DistilBERT Model
- Flask App Preparation
- Run Your First Flask Application
- Predict Sentiment at Your Local Machine
- Build Predict API
- Deploy DistilBERT Model at Your Local Machine
Deploy Your DistilBERT ML Model at AWS EC2 Windows Machine with Flask
- Create AWS Account
- Create Free Windows EC2 Instance
- Connect EC2 Instance from Windows 10
- Install Python on EC2 Windows 10
- Must Read This!!!
- Install TensorFlow 2 and KTRAIN
- Run Your First Flask Application on AWS EC2
- Transfer DistilBERT Model to EC2 Flask Server
- Deploy ML Model on EC2 Server
- Make Your ML Model Accessible to the World
Deploy Your DistilBERT ML Model at AWS Ubuntu (Linux) Machine with Flask
- Install Git Bash and Commander Terminal on Local Computer
- Create AWS Account
- Launch Ubuntu Machine on EC2
- Connect AWS Ubuntu (Linux) from Windows Computer
- Install PIP3 on AWS Ubuntu
- Update and Upgrade Your Ubuntu Packages
- Must Read This!!!
- Install TensorFlow 2, KTRAIN and Upload DistilBert Model
- Create Extra RAM from SSD by Memory Swapping
- Deploy DistilBERT ML Model on EC2 Ubuntu Machine
Deploy Robust and Secure Production Server with NGINX, uWSGI, and Flask
- NGINX Introduction
- Virtual Environment Setup
- Setting Up Flask Server
- NGINX Running Flask Application
- NGINX Running uWSGI Application
- Configuring uWSGI Server
- Start API Services at System Startup
- Configuring NGINX with uWSGI, and Flask Server
- Congrats! You Have Deployed ML Model in Production
Multi-Label Classification | Deploy Facebook's FastText NLP Model in Production
- What is Multi-Label Classification?
- FastText Research Paper Review
- Notebook Setup
- Data Preparation
- FastText Model Training
- FastText Model Evaluation and Saving at Google Drive
- Creating Fresh Ubuntu Machine
- Setting Python3 and PIP3 Alias
- Creating 4GB Extra RAM by Memory Swapping
- Making Your Server Ready
- Preparing Prediction APIs
- Testing Prediction API at Local Machine
- Testing Prediction API at AWS Ubuntu Machine
- Configuring uWSGI Server
- Deploy FastText Model in Production with NGINX, uWSGI, and Flask