Sayam Kumar's repositories
Company-Bankruptcy-Prediction
Successfully developed a machine learning model which can accurately predict whether a firm will become bankrupt or not, depending on various features such as net value growth rate, borrowing dependency, cash/total assets, etc.
Language-Detection-using-fine-tuned-XLM-Roberta-Base-Transformer-Model
Successfully developed a language detection transformer model that can accurately recognize the language in which any given text is written.
Emotion-Detection-using-fine-tuned-BERT-Transformer
Successfully developed a fine-tuned BERT transformer model which can effectively perform emotion classification on any given piece of texts to identify a suitable human emotion based on semantic meaning of the text.
Image-Caption-Generation-using-ResNet-and-LSTMs
Successfully developed an image caption generation model which can precisely generate the text caption of any particular image based on a certain vocabulary of distinct words.
Resume-Classification-using-fine-tuned-BERT
Successfully developed a resume classification model which can accurately classify the resume of any person into its corresponding job with a tremendously high accuracy of more than 99%.
SMS-Spam-Classification-using-fine-tuned-RoBERTa-Base-Transformer
Successfully developed a fine-tuned RoBERTa transformer model which can almost perfectly classify whether any given SMS is spam or not.
Black-Friday-Sales-Prediction
Successfully established a machine learning regression model which can estimate the gross Black Friday sales for a particular customer, based on a distinct set of related and meaningful features, to a fair level of accuracy.
My-Portfolio-Website
This is my portfolio website.
News-Category-Classification
Successfully developed a news category classification model using fine-tuned BERT which can accurately classify any news text into its respective category i.e. Politics, Business, Technology and Entertainment.
Walmart-Weekly-Sales-Prediction-using-Machine-Learning
Successfully established a supervised machine learning model which can accurately forecast the total weekly sales amount obtained at Walmart stores, based on a certain set of features provided as input.
Concrete-Strength-Prediction
Successfully developed a machine learning model which can accurately predict the strength of cement based on various features such as blast furnace slag, water, coarse aggregate, etc.
Credit-Card-Approval-Prediction
Successfully developed a machine learning model which can accurately predict up to 100% accuracy whether a credit card application of a given applicant would be approved or not, based on several demographic features such as applicant age, total income, marital status, total years of work experience, etc.
Credit-Score-Classification
Successfully developed a machine learning model which can accurately classify the credit score of a customer based on his/her's basic bank details and a lot of other credit-related features.
Customer-Support-Chatbot-using-NLTK
Successfully developed a chatbot model which can provide accurate and concise responses to a wide variety of customer queries regarding the services offered by a particular company as well as general topics.
E-Commerce-Text-Classification
Successfully established a machine learning model that can accurately classify an e-commerce product into one of four categories, namely "Books", "Clothing & Accessories", "Household" and "Electronics", based on the product's description.
Employee-Attrition-Prediction
Successfully established a machine learning model which can accurately predict whether an employee of a given company will leave it in the impending future or not, based on several employee details and employment metrics.
English-to-Spanish-Language-Translation-using-Seq2Seq-and-Attention
Successfully established a Seq2Seq with attention model which can perform English to Spanish language translation up to an accuracy of almost 97%.
Financial-News-Sentiment-Analysis
Successfully developed a fine-tuned DistilBERT transformer model which can accurately predict the overall sentiment of a piece of financial news up to an accuracy of nearly 81.5%.
Flight-Price-Prediction
Successfully established a machine learning model to accurately predict the price of a flight in India based on several features such as duration, days left, arrival time, departure time and so on.
Global-News-Headlines-Text-Summarization
Successfully established a text summarization model using Seq2Seq modeling with Luong Attention, which can give a short and concise summary of the global news headlines.
Life-Expectancy-Prediction
Successfully established a machine learning model which can accurately predict the expected life duration of a human being based on several demographic features such as alcohol consumption per capita, average BMI of entire population, etc.
Sales-Prediction-using-Supervised-Machine-Learning
Successfully established a supervised machine learning model which can accurately predict the gross sales generated by an XYZ company based on its weekly spends on distinct marketing channels across a span of 4 years from 2015 to 2019.
SQuaD-Question-Answering-using-BERT
Successfully leveraged a pretrained BERT Transformer model for developing a question answering system.
Superstore-Sales-Prediction
Successfully established a machine learning model that can accurately predict the sales of a superstore based on various features such as quantity, profit, discount, postal code, etc. The features are mainly associated with order details and customer demographics.
Symptoms-Disease-Text-Classification
Successfully developed a fine-tuned BERT transformer model which can accurately classify symptoms to their corresponding diseases upto an accuracy of 89%.
Taxi-Trip-Fare-Prediction
Successfully created a machine learning model which can accurately predict the fare of a taxi trip based on several features such as trip duration, tip amount, etc.
Techosto-Python-Development-Internship-Assessment
Successfully implemented various time series models such as Exponential Smoothing, Holt-Winters, ARIMA, SARIMA, etc. to forecast the closing stock prices of Quick Heal Technologies Pvt. Ltd. and HDFC Bank.
Travel-Insurance-Claim-Prediction
Successfully established a supervised machine learning model that can accurately predict whether the travel insurance claim of a particular customer should be approved or not by a travel insurance agency.
Weather-Prediction-using-Machine-Learning
Successfully developed a machine learning model which can accurately classify the weather based on various features pertaining to weather-related data and atmospheric conditions.
Wine-Quality-Prediction
Successfully established a supervised machine learning model which can predict the quality of a wine to a high level of accuracy based on a certain set of features associated with the chemical properties and characteristics of that specific wine.