ashishpatel26's Repositories

100 days of algorithms

Fork this template for the 100 days journal - to keep yourself accountable (multiple languages available)

100 Days of ML Coding

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100+ python programming exercise problem discussed ,explained and solved in different ways

A repository dedicated to the #100DaysofMLCode Challenge.

14 days Beginner Practical Guide of Machine Learning

1d CNN Network for Audio Classificaiton

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Email Newsletter

this is a 2D Vnet model of Keras Version,The architecture of the model is the same as the original 3D Vnet, except that this is a network for 2D image segmentation (the convolution kernel becomes 2D)

30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace.

365 Days Computer Vision Learning Linkedin Post

3D Deep Learning works

3D super-resolution using Generative Adversarial Networks

A resource repository for 3D machine learning

Keras implementation of the paper "3D MRI brain tumor segmentation using autoencoder regularization" by Myronenko A. (https://arxiv.org/abs/1810.11654).

List of projects for 3d reconstruction

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Keras 3D U-Net Convolution Neural Network (CNN) designed for medical image segmentation

The 500 AI Agents Projects is a curated collection of AI agent use cases across various industries. It showcases practical applications and provides links to open-source projects for implementation, illustrating how AI agents are transforming sectors such as healthcare, finance, education, retail, and more.

500 AI Machine learning Deep learning Computer vision NLP Projects with code

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Official implement of Paper：A deeply supervised image fusion network for change detection in high resolution bi-temporal remote sening images

✅ Curated list of resources for college students

360 view on ai/ml/dl applications

tensorflow implementation of speech/nonspeech segmentation for audio files

Source code complementing our paper for acoustic event classification using convolutional neural networks.

Huggingface Transformers + Adapters = ❤️

Advanced Machine Learning and Signal Processing

Advanced Machine Learning and Signal Processing IBM

GitHub Repository to host all contents for SPAI Advance Machine Learning Workshop

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Advanced Retrieval-Augmented Generation (RAG) through practical notebooks, using the power of the Langchain, OpenAI GPTs ,META LLAMA3 ,Agents.

Adversarial Threat Landscape for AI Systems

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

Full toolkit for running an AI agent service built with LangGraph, FastAPI and Streamlit

Flexible and powerful framework for managing multiple AI agents and handling complex conversations

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Building reliable Retrieval Augmented Generation(RAG) AI Architecture

Agentic RAG with MCP Server

Repository demonstrating best practices and patterns for implementing agentic workflows in Python, featuring modular, scalable, and reusable design patterns for intelligent automation.

Implementing the 4 agentic patterns from scratch

Repo for the Complete Agentic AI Engineering Course

Agno is a lightweight library for building multi-modal Agents

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roadmap to applied ai

Projects & Resources to help you become a better AI Developer.

Collection of AI Agent and RAG

Roadmap to becoming an Artificial Intelligence Expert in 2020

12 Weeks, 24 Lessons, AI for All!

Learn to build, evaluate, and integrate predictive models that have the power to transform patient outcomes. Begin by classifying and segmenting 2D and 3D medical images to augment diagnosis and then move on to modeling patient outcomes with electronic health records to optimize clinical trial testing decisions. Finally, build an algorithm that uses data collected from wearable devices to estimate the wearer’s pulse rate in the presence of motion.

This repositary consists of all the solutions of the Quiz and Programming Assignments for the "AI for Medical Diagnosis" in Coursera by deeplearning.ai. Please use this only for reference Purpose

A Python package that makes it easy for developers to create AI apps powered by various AI providers.

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Watson OpenScale tutorials including sample models, notebooks and applications

This is a repository for the course "From Beginner to LLM Developer" by Towards AI.

Codes/Notebooks for AI Projects

Testing the different LLM and RAG Tests while I learn along the way

AI Agent with comprehensive observability using LangGraph, CrewAI, and Langfuse

AI Agent Work shop include Agent from Corepython, using CrewAI and Using SmolAgent

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AI MultiModel Demo

A prototype developed by me to collect the real-time data of the different types of pollution gases present in the air and analyzing and visualizing them and doing certain predictions.

[BA project] Dynamic Pricing Optimization for Airbnb listing to optimize yearly profit for host. Use Clustering for competitive analysis, kNN regression for demand forecasting, and find dynamic optimal price with Optimization model.

Airbnb is one of the fastest growing companies and has been increasing it's user base rapidly. Airbnb’ing continues to expand in popularity among both leisure and business travelers. Airbnb gives independence to the host to price their listing. This provides interesting use cases to solve for both the hosts as well as the guests. I took up two use cases 1) Predicting competitive price for a listing based on the characteristics of the listing which helps the hosts when they enter the market. 2) Forecasting prices of listings based on the multivariate time series data to help the guests plan their trip and accommodation. The tasks performed in implementing the project are: 1. Exhaustive Data Exploration, Data preprocessing and Data Wrangling of the Airbnb dataset. 2. Used Ensemble models such as Random Forest, XGBoost and LightGBM for price prediction. Also used Ridge Regression and KNN. Computed Median Squared Error and Mean Squared Error of the test data. 3. Performed hyperparameter tuning on all 5 models using ARC(A Root Cluster for Research into Scalable Computer Systems) and the results showed a marked improvement. 4. Used Arima (AutoRegressive Integrated Moving Average) and BSTS (Bayesian Structural Time Series) to capture the seasonal effects and trends in the data which helped in forecasting the prices of the listings with great accuracy.

Detection and segmentation of ship instances in satelite images using Keras Retinanet and Keras MaskRcnn.

A machine learning exercise presenting a simple model for (1) prediction of airfares from the data contained in the search query using linear support vector regression implementation sklearn.SVM.LinearSVR and (2) classification of flight itinerary search results by likelihood the returned fare will ultimately be purchased by the consumer, using simple Naive Bayes implementation in sklearn.

Cookbooks for AI Agents

Open Deep Learning and Reinforcement Learning lectures from top Universities like Stanford, MIT, UC Berkeley.

This is the code for "AI for Supply Chain" by Siraj Raval on Youtube

Tutorial on how to deploy Deep Learning models on GPU enabled Kubernetes cluster

[CVPR2020] Adversarial Latent Autoencoders

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Code examples for training AlexNet using Keras and Theano

DSA Practise book for interview

Source code for Algorithmic Trading with Python (2020) by Chris Conlan

Collection of algorithms and data structures implemented in Python and C++

Open source content from a book in progress, Hands-on Algorithmic Problem Solving

Implementation of 17+ agentic architectures designed for practical use across different stages of AI system development.

Self-study on Larry Wasserman's "All of Statistics"

Notebooks for the Altair tutorial

The Additive Margin MobileNet1D is a new light weight deep learning model for Speaker Recognition which is based on the MobileNetV2 architecture and the Additive Margin Softmax (AM-Softmax) loss function.)

Amazing Collection Vehicle Routing Problem

Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.

🚀 Curated collection of Amazing Python scripts from Basics to Advance with automation task scripts.

PyTorch Tutorial for Deep Learning Researchers

Amazing Semantic Segmentation on Tensorflow && Keras (include FCN, UNet, SegNet, PSPNet, PAN, RefineNet, DeepLabV3, DeepLabV3+, DenseASPP, BiSegNet)

TensorFlow Tutorial and Examples for Beginners with Latest APIs

Clustering using tslearn for Time Series Data.

The machine learning notebook for the course of Andrew Ng

This is Andrew NG Coursera Handwritten Notes.

Repository for the code developed in the context of my thesis entitled "Malware Detection in Android Applications with Machine Learning Techniques" for the MSc in Computer Science and Engineering at Lisbon Institute of Engineering (ISEL).

Wining solution and its further development for MICCAI 2017 Endoscopic Vision Challenge Angiodysplasia Detection and Localization

notebooks and some data for playing with animeface stylegan2 and deepdanbooru

🧠 Implementations/tutorials of deep learning papers with side-by-side notes; including transformers (original, xl, switch, feedback), optimizers(adam, radam, adabelief), gans(dcgan, cyclegan, stylegan2), reinforcement learning (ppo, dqn), capsnet, sketch-rnn, etc.

Intrusion Detection System using Machine Learning and Deep Learning

Anomaly detection related books, papers, videos, and toolboxes

Anomaly or Outlier Detection Research Paper and Code

Medical image analysis framework merging ANTsR and deep learning