Putuputrayasa's Stars
yradwan147/EmailCommandServer
Automation, Email Parsing, Web Scraping, Utility | Python project to read commands from a gmail and execute commands on local computer. Includes features like: sending latest music download links from computer to phone, recommending best product buys based off of online reviews, and recommending the best transport service based on cost. All responses were sent through email.
abrarzahin/Recommendation-system
Built a machine learning recommendation system using python and PyCharm. This system will be able to recommend new movies to users based on the reviews of movies they have already seen. But the exact same system can be used for any type of product or service that a company want to recommend to a user.
btwitsrishabh/Youtube-GPT-Creator
This repository contains a Python script that uses the Langchain framework to automatically generate YouTube video titles and scripts. The script uses the GPT-3.5 language model to generate the text, and it can be customized to generate different types of content, such as educational videos, product reviews, or vlogs.
mdiby/Machine-Learning-A-Case-Study-Approach
In this course, you will get hands-on experience with machine learning from a series of practical case-studies. At the end of the first course you will have studied how to predict house prices based on house-level features, analyze sentiment from user reviews, retrieve documents of interest, recommend products, and search for images. Through hands-on practice with these use cases, you will be able to apply machine learning methods in a wide range of domains. This first course treats the machine learning method as a black box. Using this abstraction, you will focus on understanding tasks of interest, matching these tasks to machine learning tools, and assessing the quality of the output. In subsequent courses, you will delve into the components of this black box by examining models and algorithms. Together, these pieces form the machine learning pipeline, which you will use in developing intelligent applications. Learning Outcomes: By the end of this course, you will be able to: -Identify potential applications of machine learning in practice. -Describe the core differences in analyses enabled by regression, classification, and clustering. -Select the appropriate machine learning task for a potential application. -Apply regression, classification, clustering, retrieval, recommender systems, and deep learning. -Represent your data as features to serve as input to machine learning models. -Assess the model quality in terms of relevant error metrics for each task. -Utilize a dataset to fit a model to analyze new data. -Build an end-to-end application that uses machine learning at its core. -Implement these techniques in Python.
jeongwang95/AmazonShopping
Given a shopping list, this automation robot scrapes top 25 products of each item on Amazon. Then, the program decide which one to buy based on its rating, number of reviews, and price. UiPath writes all the needed data from Amazon to Excel, then we have a python script that determines its "score."
sherlock237/FASHION-GENRE
This is an E-COMMERCE WEBSITE name Fashion Genre. In which User can SEARCH , TRACK , MAINTAIN CART AND WHISLIST, REVIEW ITEM , LIKE AND DISLIKE PRODUCT and many more. This is an DJANGO framework Language Used is PYTHON , HTML, CSS , JAVASCRIPT and for Database MYSQL.
blue-samarth/Amazon_scraper-
This is a Python web scraper that extracts data from Amazon.in based on a user-defined search term, including product name, description, URL, price, rating, reviews, and manufacturer information. It uses requests to get HTML, BeautifulSoup to parse it, and msedge.selenium_tools to navigate the web pages and save the data to a CSV file.
sidkadam69/Twitter-sentiment-analysis-using-NLTK-preprocessing-
Twitter Sentiment analysis(preprocessing using NLTK) Introduction:- 1. Sentiment Analysis is the process of determining whether a piece of writing is positive, negative. Why Twitter? 1. Popular microblogging site 2. 240+ million active users 3. 500 million tweets are generated everyday 4. Twitter audience varies from common man to celebrities 5. User often discuss current affairs and share personal views. 6. Tweets are small in length and hence unambiguous 7. Political party may want to know whether people support their program or not 8. A company might want find out the reviews of its products Problem statement 1. Given a message, decide whether the message is of positive or negative sentiment. For messages conveying both a positive and negative sentiment, whichever is the stronger sentiment should be chosen 2. Aim is to detect hate speech in Tweets. For the sake of simplicity, we say a tweet contains hate speech if it has a racist or sexist sentiment associated with it. Challenges 1. People express opinion in complex ways 2. In opinion texts, lexical content alone can be misleading 3. Out of Vocabulary Words 4. Unstructured and also non-grammatical 5. Extensive usage of acronyms like asap, lol, idk 6. Using special characters, mentions, tags 7. Lexical variation Setup Twitter API 1. Create Twitter account and login 2. Fill Twitter application form to get access key for verification 3. Get keys after successfully fill application form 4. We get API key, API secrete key, access token, access token secrete. Conclusion 1. We will obtain a polarity of sentiment and display it on our webpage with 0 and 1 ( positive and negative respectively) with the help of flask framework in python and pipeline. 2. In this project we showed the importance of preprocessing of data . 3. Accuracy has increased after preprocessing and we have better results with analysis.
elberttl/Tokopedia-Product-Reviews-Finder
A Python script to find reviews on a Tokopedia product
aldipermanaetikaputra/product-review-classification
Product Review Classification - Sentiment Analysis on FMCG Product Review at Tokopedia Marketplace
zhanymkanov/marketplace_parser
Products and Reviews Crawler
siddh30/Amazon-Sentiment-Analysis
A Natural Language Processing based project - Sentiment Analysis of Amazon Product Reviews in Python
praneethravuri/Amazon-Product-Information-Scraper
This Python web-scraping project retrieves product names, prices, review stars, and review counts for a specific product category.
aflansburg/amzreviewsscrape
Scrape Amazon Product Reviews using Python and the Selenium WebDriver for Chrome
irecasens/nlp_amazon_reviews
Mobile phone reviews from Amazon.com are analysed to find trends and patterns and determine which characteristics are mentioned most by customers and with what sentiment for each product.
oxylabs/amazon-scraper
Free Trial Amazon Scraper API for extracting search, product, offer listing, reviews, question and answers, best sellers and sellers data.
theimperium20/Aliexpress-Review-Crawler
A Python script to scrape all reviews from the given aliexpress product url and write them in a csv file..
SinghalHarsh/amazon-product-review-scraper
Python package to scrape product review data from amazon
officialpm/scrape-amazon
🤩 Python Package for Scraping Amazon Product Reviews ✨
yasharmaster/Fk-Review-Scraper
Python script for scraping product reviews
RudrenduPaul/Python-Ecommerce-recommendation-system-using-machine-learning
Business setting up their recommendation system for first time without any product rating history, & Amazon/Netflix type of recommendation system after the website has collected significant product reviews
mandeep147/Amazon-Product-Recommender-System
Sentiment analysis on Amazon Review Dataset available at http://snap.stanford.edu/data/web-Amazon.html
Shopify/product-reviews-sample-app
A sample Shopify application that creates and stores product reviews for a store, written in Node.js
mominalix/bulk-email-generator-using-ChatGPT
This repository shows how to create personalized emails in bulk using Open AI ChatGPT API and web scrapping.
vithika-karan/Email-Campaign-Effectiveness-Prediction
Most of the small to medium business owners are making effective use of Gmail-based Email marketing Strategies for offline targeting of converting their prospective customers into leads so that they stay with them in Business. The main objective is to create a machine learning model to characterize the mail and track the mail that is ignored; read; acknowledged by the reader.
swapypatil/crm-marketing
CRM - Email Marketing is a python application intended for business holders to save their customer data and advertise their business to the customer with email marketing.
lillee205/emailDigest
A short Python script which compiles specified marketing emails into one weekly digest into my personal email.
VlcKVlck/marketingrobot
Email automation, mostly intended for marketing purposes. Python, Django, Gmail API, Postgres.
Matra888/email_SQL_Python
SQL segments your customer database for targeted email marketing, enhancing message relevance and sales. Python's machine learning algorithms tag and cluster customers, enabling personalized marketing strategies that boost customer engagement and sales.
debayan53/Email_marketing
This is a python code which Retail or wholesale business can use to do email marketing like send a follow up massage after customer visited your showroom or a reminder mail for the prepaid/postpaid plan recharge ,specific customized mail can also be sent using option no4 and all these can be send 100+ customer without opening gmail and manually adding and typing customer's email