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alt_genai_voicebot

anik424

Config files for my GitHub profile.

asl-ml-immersion

This repos contains notebooks for the Advanced Solutions Lab: ML Immersion

autogen

Enable Next-Gen Large Language Model Applications. Join our Discord: https://discord.gg/pAbnFJrkgZ

autogen-rag-multi

autots

Automated Time Series Forecasting

azure-ml

ball-tracking

banking-market-analysis-using-scala

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.

bike-rental-prediction-based-on-env-season

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.

brain_mri_tumor

classifying-reviews-of-cars-and-digital-camera

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'.

classifying_images_from_mnist_fashion_dataset

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-of-bbc-news-articles

Clustering BBC News articles using different types of vectorization, dimensionality reduction and clustering algorithms. Then giving appropriate names to the clusters.

credit-eda-case-study

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.

databricks-handson

detectron

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

dnn-example-with-tensorflow-1.x

Building a deep neural network using TensorFlow 1.x for binary classification.

docs

Source code for the Streamlit Python library documentation

eda-comcast-consumer-complaints-analysis

This EDA has been performed on Comcast Consumer Complaints dataset.

face-emotion-detection-using-cnn

flowise

Drag & drop UI to build your customized LLM flow using LangchainJS

generative-ai-light-edition

Generative AI Notebooks that do not need massive instances

google-vision-data-extractor

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.

hand-gesture-recognition-system

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.

hh-rlhf

Human preference data for "Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback"

hmm_pos_tagging

HMM based POS tagging using Viterbi Algorithm

house-price-prediction-ridge_lasso

Housing price prediction model using Ridge and Lasso Regression.

image-denoising-using-convolutional-autoencoder

The objective is to add some noise to the images and then use an Convolutional Autoencoder to denoise them.

indoor-scene-recognition

The dataset has a collection of about 15000+ labeled images belonging to 67 categories. I am selecting only below 10 categories ⚰ airport_inside, auditorium, bakery, bathroom, bookstore, casino, church_inside, grocerystore, operating_room, warehouse Objective is to create a model that will able to classify images into these 10 categories.