Udemy - Data Science - Sentiment Analysis - Model Building Deployment

Data Science: Sentiment Analysis - Model Building Deployment
Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 782 MB | Duration: 1h 33m
A practical hands on Data Science Project on Sentiment Analysis using NLP techniques - Model Building & Deployment
What you'll learn
Data Analysis and Understanding
Data Preprocessing Techniques
POS tagging and Lemmatization
Word Cloud
TF-IDF Vectorizer
Model Building for Sentiment Analysis
Classification Metrics
Model Evaluation
Running the model on a local Streamlit Server
Pushing your notebooks and project files to GitHub repository
Deploying the project on Heroku Cloud Platform

Description
In this course I will cover, how to develop a Sentiment Analysis model to categorize a tweet as Positive or Negative using NLP techniques and Machine Learning Models. This is a hands on project where I will teach you the step by step process in creating and evaluating a machine learning model and finally deploying the same on Cloud platforms to let your customers interact with your model via an user interface.

This course will walk you through the initial data exploration and understanding, data analysis, data pre-processing, data preparation, model building, evaluation and deployment techniques. We will explore NLP concepts and then use multiple ML algorithms to create our model and finally focus into one which performs the best on the given dataset.

At the end we will learn to create an User Interface to interact with our created model and finally deploy the same on Cloud.

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