Arjit Y.

Highly experienced in web scraping and data mining. Specializing in solving problems using machine learning (ML), natural language processing (NLP), computer vision (CV) across different industries, developing end- to-end solutions from formulating the problems/requirements (along with the stakeholders) to scalable deployment of the products. ✅ AREAS OF EXPERTISE Data Science, Data Engineering, Data Visualization, Machine Learning, Deep Learning, Data Mining, Web Scraping ✅* Packages Use for SCRAPING: Requests, BeautifulSoup, Selenium, Scrapy, Twint, Instagram-scraper ✅ Experience with Scraping a. Social Media: Twitter, Instgram, Facebook b. App Reviews: Google Play, App Store c. E-commerce: Shopify, Amazon d. Real Estate: Realtor.com, Har.com, zillow e. Business: Yelp.com f. Restaurant: Getir g. Crypto:Coinmarketcap, Opensea h. News: cointelegraph.com i. Jobs: Indeed, Glassdoor j. Investors: signal.nfx.com k. Miscellaneous: Openwheathermap.com ✅ TECHNICAL SKILLS Programming Languages - Python, C/C++, Java, R Framework- Flask, Django ✅ Packages and tools - Pandas, NumPy, SciPy, Scikit-Learn, NLTK, matplotlib, Seaborn, ggplot2, Pyspark, Keras, Tensorflow, BeutifulSoup, Selenium, Scrapy, Requests Good with API development ✅ Machine Learning - Dimensionality reduction - Principal Component Analysis(PCA), K-Nearest Neighbors(KNN), Support Vector Machines(SVM), Naïve Bayes(NB), Decision Trees(DT), Random Forest(RF), Gradient Boosting Machines(GBM), XGBoost, Deep Learning – Deep Neural Networks & Convolution Neural Networks (CNN), Hierarchical & K-Means clustering, RFM, Market Basket Analysis - Association Rule Mining ✅ Statistical Modelling - Linear Regression, Logistic Regression, Multi-nominal Logistic Regression, Regularization - Ridge Regression, Lasso Regression, Time Series forecasting ✅ Text Mining - Text Pre-Processing, Information Retrieval, Text Classification, Topic Modeling (Latent Dirichlet Allocation(LDA), Non-negative Matrix Factorization(NMF)), Text Clustering, Sentiment Analysis ✅ DATABASE SQL, PostgresAQl, MongoDB, DynamoDB