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Name: Anik Chakraborty
Type: User
Bio: Data Science, Machine Learning, Deep Learning, NLP, Python, Azure ML, SciKit-Learn, TensorFlow, Keras, OpenCV, SQL, Power BI
Name: Anik Chakraborty
Type: User
Bio: Data Science, Machine Learning, Deep Learning, NLP, Python, Azure ML, SciKit-Learn, TensorFlow, Keras, OpenCV, SQL, Power BI
Config files for my GitHub profile.
This repos contains notebooks for the Advanced Solutions Lab: ML Immersion
Enable Next-Gen Large Language Model Applications. Join our Discord: https://discord.gg/pAbnFJrkgZ
Automated Time Series Forecasting
Your client, a Portuguese banking institution, ran a marketing campaign to convince potential customers to invest in a bank term deposit scheme. The marketing campaigns were based on phone calls. Often, the same customer was contacted more than once through phone, in order to assess if they would want to subscribe to the bank term deposit or not. You have to perform the marketing analysis of the data generated by this campaign.
Building a model to predict demand of shared bikes. It will be used by the management to understand how exactly the demands vary with different features. They can accordingly manipulate the business strategy to meet the demand levels.
Epinions.com is a website where people can post reviews of products and services. It covers a wide variety of topics. For this case study, we downloaded a set of 600 posts about digital cameras and cars and saved as “Eopinions.csv”. The dataset has 2 columns: ‘class’ and ‘text’. We need to predict 'class' based on 'text'.
The dataset is similar to MNIST but includes images of certain clothing and accessory. The objective is to classify images into specific classes using a single-layer perceptron & multilayer perceptron.
Clustering BBC News articles using different types of vectorization, dimensionality reduction and clustering algorithms. Then giving appropriate names to the clusters.
This case study aims to identify patterns which indicate if a client has difficulty paying their instalments which may be used for taking actions such as denying the loan, reducing the amount of loan, lending (to risky applicants) at a higher interest rate, etc. This will ensure that the consumers capable of repaying the loan are not rejected. Identification of such applicants using EDA is the aim of this case study. In other words, the company wants to understand the driving factors (or driver variables) behind loan default, i.e. the variables which are strong indicators of default. The company can utilise this knowledge for its portfolio and risk assessment.
FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.
Building a deep neural network using TensorFlow 1.x for binary classification.
Source code for the Streamlit Python library documentation
This EDA has been performed on Comcast Consumer Complaints dataset.
Drag & drop UI to build your customized LLM flow using LangchainJS
Generative AI Notebooks that do not need massive instances
This python code can be used to extract data from Google Vision output. After you process your file for OCR using Google Vision, the generated text extraction can be structured and attributes can be identified by using this code. Please check Read me for the details.
Imagine you are working as a data scientist at a home electronics company which manufactures state of the art smart televisions. You want to develop a cool feature in the smart-TV that can recognize five different gestures performed by the user which will help users control the TV without using a remote.
Human preference data for "Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback"
HMM based POS tagging using Viterbi Algorithm
Housing price prediction model using Ridge and Lasso Regression.
The objective is to add some noise to the images and then use an Convolutional Autoencoder to denoise them.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.