sayamalt Goto Github PK

8-cities-photography-data-analysis

abstractive-text-summarization-of-news-articles

Successfully developed an encoder-decoder based sequence to sequence (Seq2Seq) model which can summarize the entire text of an Indian news summary into a short paragraph with limited number of words.

amazon-sales-data-analysis

In this project, I have analyzed Amazon sales records, defined KPIs(Key Performance Indicators) and established meaningful relationships between them for deriving useful statistical insights.

applied-data-science-capstone-project

This repository contains all the Python files, dashboards and reports associated with the IBM Data Science Capstone project.

bank-customer-segmentation

Successfully established a clustering model which can categorize the customers of a renowned Indian bank into several distinct groups, based on their behavior patterns and demographic details.

beauty-classification

Successfully established a deep learning model which can accurately predict whether a woman's face is beautiful or average.

bizanalytics-ml-assessment-solution

Successfully developed a machine learning model which can classify whether an email is spam or ham.

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.

car-license-plate-detection

Successfully established a deep learning model which can detect the license number plates of cars.

car-price-prediction

Successfully developed a Linear Regression Model which can be used to predict the price of cars based on a set of independent variables.

children-adult-classification

Successfully established a deep learning model which can precisely classify a human being as a child or an adult.

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.

computer-vision

This repository covers all the concepts taught in renowned Udemy instructor Josa Portilla's course on Computer Vision.

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-card-fraud-detection

Established a machine learning model which can predict whether a credit card transaction is fraudulent or not to a significant level of accuracy.

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.

crop-yield-prediction

Successfully created a regression model for performing predictions on the net area yield of any particular crop.

customer-churn-prediction

Successfully established a machine learning model which can predict whether any given customer currently utilizing the products and services offered by a company will churn at anytime in the future or not, depending upon a set of unique features/characteristics pertaining to that specific individual, to a great level of accuracy.

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.

databases-sql-using-python

Working with databases through DB API using Python. Mainly, I worked with a database instance created at IBM DB2 cloud, created and loaded several datasets within it and issued SQL queries for accessing and manipulating data of each provided dataset.

detection-of-disaster-from-tweets

Successfully established a machine learning model for detecting whether a given tweet is about a real disaster or not.

driver-drowsiness-detection

Successfully established a deep learning model which can accurately predict the drowsiness state of an individual and thereby alert a driver who is in a drowsy state for preventing fatal accidents.

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.

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.

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-premier-league-data-analysis

Complete Analysis of English Premier League data of 20 years.

english-to-french-language-translation-using-seq2seq-modeling

Established a deep learning model which can translate English words/sentences into their corresponding French translations.

english-to-german-translation-using-seq2seq

Successfully established a neural machine translation model using sequence to sequence modeling which can successfully translate English sentences to their corresponding German translations.

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%.