Welcome to the repository covering a wide array of topics including Machine Learning, Deep Learning, Computer Vision, Natural Language Processing (NLP), and Research Projects. This comprehensive collection serves as a hub for exploring various facets of artificial intelligence and research endeavors.
This repository aims to provide a holistic view of cutting-edge technologies and research trends in the fields of Machine Learning, Deep Learning, Computer Vision, NLP, and beyond. Whether you're a novice eager to learn or a seasoned practitioner seeking inspiration, this repository offers a diverse range of projects and resources to cater to your interests and expertise.
Multifaceted Coverage: Dive into a rich spectrum of topics including traditional Machine Learning algorithms, advanced Deep Learning architectures, Computer Vision techniques, NLP applications, and research projects spanning different domains.
Hands-On Projects: Explore practical implementations of algorithms, models, and techniques through hands-on projects, code examples, and Jupyter notebooks, designed to enhance your understanding and foster experimentation.
Research Endeavors: Engage with research projects, papers, datasets, and experiments, providing insights into the latest advancements and methodologies in artificial intelligence and related fields.
Collaborative Environment: Foster collaboration, knowledge sharing, and community engagement through contributions, discussions, and feedback, promoting continuous learning and innovation.
Machine Learning: Implementations of classical and contemporary Machine Learning algorithms for tasks such as regression, classification, clustering, and reinforcement learning.
Deep Learning: Explore advanced Deep Learning architectures, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and transformer models.
Computer Vision: Delve into Computer Vision projects and techniques for image classification, object detection, image segmentation, facial recognition, and more.
Natural Language Processing: Discover NLP applications such as text classification, sentiment analysis, named entity recognition, machine translation, and text generation.
Research Projects: Engage with research-oriented projects, experiments, and papers addressing contemporary challenges and exploring novel solutions across diverse domains.
Explore the repository's contents, delve into projects and resources aligned with your interests, and leverage the provided materials to enhance your skills and knowledge in Machine Learning, Deep Learning, Computer Vision, NLP, and research endeavors.
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๐ Comprehensive AI Curriculum: Dive deep into Machine Learning, Deep Learning, NLP, Computer Vision, and moreโfrom foundational concepts to advanced, industry-level techniques.
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๐ Hands-On Real-World Projects: Each topic is backed by practical projects, complete with Jupyter notebooks, datasets, and implementation guides. Build everything from spam detectors and sentiment analyzers to real-time emotion detection and recommender systems.
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๐ค Global Collaborative Learning: Connect and collaborate with learners, researchers, and developers across the globe through GitHub issues, discussions, and community forums. Contribute code, suggest improvements, or explore new topics together
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๐ฅ AI-Powered Course: Stay ahead with industry-relevant techniques like transformers, BERT, GPT, and more. Convert this for computer vision so that it attract contributor
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๐ Open Source Contribution Friendly: Whether you're a beginner looking to learn or a pro ready to contribute, this course is designed to support your journey. Add new features, optimize models, write tutorials, or simply share resourcesโthe repo is built by the community, for the community.
๐ Fork & Star this repository
๐ Explore the Projects: Browse through a wide variety of practical projects across Machine Learning, Deep Learning, NLP, Computer Vision, and Python scripts.
๐ Enhance Existing Projects: Improve current code, optimize models, refactor scripts, fix bugs, or update notebooks with better documentation and explanations.
๐ง Add New Projects: Build something cool in AI or data science? Submit your own projects using Pythonโwhether it's a new classifier, preprocessing pipeline, chatbot, or real-time application.
๐ Write Technical Blogs or Tutorials: Create accompanying write-ups, tutorials, or guides explaining the working of any projectโhost it on Medium, Substack, or your blog, and link it here.
๐ค Collaborate with Other Contributors: Join discussions, solve open issues, review pull requests, and brainstorm new ideas for AI-powered applications.
๐ Share Learning Resources: Contribute useful blogs, videos, courses, GitHub repositories, or research papers related to AI, ML, CV, NLP, or Python.
๐ Share valuable blogs, videos, courses, GitHub repositories, and research websites
Contributions are encouraged and appreciated! Whether it's adding new projects, improving existing content, fixing bugs, or suggesting enhancements, your contributions play a vital role in enriching the repository for the benefit of the community. Please contact me on my skype ID:themushtaq48, email:mushtaqmsit@gmail.com for contribution.
Together, let's make this the best AI learning hub repository! ๐
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Project Title / Blog | Description | Notebook | Category | To-Do List | Resource Link | Completed |
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๐1 - Stock Price Prediction using Linear Regression | Accuracy = 0.99, Model = Linear Regression; Techniques: Scikit-learn, Label Encoding, MICE (Multiple Imputation) | Regression | ๐ Try other models (XGBoost, SVR), add visualization, deploy using Streamlit | โ | โ | |
๐2 - Predict Ads Click โ Practice Data Analysis | Classification with Logistic Regression; Techniques: Data Cleaning, Feature Engineering, Label Encoding, MICE | Classification | ๐ Try different classifiers (Random Forest, XGBoost), improve feature selection | โ | โฌ Pending | |
๐3 - LinkedIn Auto Job Applier with AI | Automation script using ML for job applications; Techniques: Scikit-learn, Label Encoding, Automation Tools | Classification / Automation | ๐ Improve job-matching logic, add real-time application tracking, convert to GUI | โ | โฌ Pending |
Project Title | Description | Code | Category | To do list | Creator | Added | Completed |
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๐1- Credit Card Fraud Detection | Autoencoders,Keras | Preprocessing | Add more Preprocessing steps | Dr.Mushtaq | 2024-06-08 | Pending |
Project Title | Description | Code | Category | To do list | Creator | Added | Completed |
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๐1- Build a simple image Classifer | Accuracy 13-80%,Model=multilayer perceptron, Keras, | Classification | Try other Deep learning model,CNN,etc | Dr Mushtaq | 2020-09-06 | โ | |
๐2- Convert Color Image to Sketch | gaussian filter,dogding | Filtering | Try technique | Dr.Mushtaq | 2024-04-20 | โ | |
๐3- Building a Real Time Emotion Detection with Python | CNN=57.67,Kera | Classification | -Real time detection not working(Need to correct in colab)- Try others DL techniqueS | Dr.Mushtaq | 2024-04-27 | โ | |
๐4- Age, Gender and Race Prediction | Age Prediction=CNN= ACC=.91,Gender Prediction=CNN Acc=,86, Ethnicity Prediction CNN Acc=0.74,Kera | Classification | -Real time detection not working(Need to correct in colab)- Try others DL techniqueS | Dr.Mushtaq | 2024-06-2 | โ | |
๐5- Image Preprocessing using Python-s | Python,scikit-image | Preprocessing | Add more Preprocessing steps | Dr.Mushtaq | 2024-06-08 | โ | |
๐6- Traffic Sign Classification with Keras and Deep Learning | Python,scikit-image,OpenCV,NumPy, CNN Test acc:.97 | Classification | Add more Preprocessing steps and Computer Vision methods | Dr.Mushtaq | 2024-08-16 | โ | |
๐7- Moment-based feature extraction for image classification | Zernike moments are widely used for shape representation due to their rotation-invariant properties. This implementation extracts Zernike features from grayscale images and applies them in a transformer-based classification model.** | Classification | Add more Preprocessing steps and Computer Vision methods | AtharvMalusare | 2025-04-1 | โ |
Project Title / Blog | Description | Notebook | Category | To-Do List | Creator | Added | Difficulty Ratings | Completed |
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๐1 - Spam Detection using Machine Learning Methods | Naive Bayes = 95โ97%, SVM = 98โ99%, using CountVectorizer, Scikit-learn, Grid Search CV | Text Classification | Try other models, enhance preprocessing | Dr. Mushtaq | 2024-04-12 | โ | ||
๐2 - Hate Speech Detection | Decision Tree = 75%, CountVectorizer, Scikit-learn | Text Classification | Test with different classifiers and preprocessing | Dr. Mushtaq | 2024-04-21 | โ | ||
๐3 - Detecting Sports Content | SVM = 66%, CountVectorizer, Scikit-learn | Text Classification | Try new models and advanced preprocessing | Dr. Mushtaq | 2024-04-28 | โ | ||
๐4 - Personality Prediction Through CV | SVM = 66%, CountVectorizer, Scikit-learn | Text Classification | Try other models, preprocessing methods | Dr. Mushtaq | 2024-04-28 | โฌ Pending | ||
๐5 - Predicting Movie Reviews with ML | Gaussian = 0.78, Multinomial = 0.83, Bernoulli = 0.84 | Sentiment Analysis | Explore more ML & DL models | Dr. Mushtaq | 2024-05-05 | โ | ||
๐6 - Text Preprocessing 101 | Covers tokenization, stemming, lemmatization, stopword removal, POS tagging | Preprocessing | -- | Dr. Mushtaq | 2024-05-26 | โญ๏ธ (Easy) | โ | |
๐7 - Important Python Scripts for NLP | Utility scripts (Text-to-Speech etc.) | Script | -- | Dr. Mushtaq | 2024-05-26 | ๐ In Process | ||
๐8 - Stress Detection using ML | Detecting stress levels via text data | Script | -- | Dr. Mushtaq | 2024-05-26 | โฌ Pending | ||
๐9 - Next Word Prediction | Predict the next word in a sequence | Script | -- | Dr. Mushtaq | 2024-05-26 | โฌ Pending ๐ | ||
๐10 - Emotion Detection in Text | Compare TF-IDF & CountVectorizer with NB, SVM, LR, RF | Sentiment Analysis | -- | Dr. Mushtaq | 2024-09-16 | โ | ||
๐11 - Auto Apply for Jobs with AI | Automates job applications | Script | -- | Dr. Mushtaq | 2024-05-26 | โฌ Pending | ||
๐12 - Chatbot for Healthcare | NLP-based chatbot for healthcare support | Script | -- | Dr. Mushtaq | 2024-05-26 | โญโญโญ (Hard) | โฌ Pending | |
๐13 - File Organizer Script | Script to organize files into folders | Script | -- | Dr. Mushtaq | 2024-05-26 | โฌ Pending | ||
๐14 - Plagiarism Checker | NLP script to check for plagiarism | Script | -- | Dr. Mushtaq | 2024-05-26 | โฌ Pending | ||
๐15 - Multilingual POS Tagging App | FastAPI app using Stanford's Stanza for multilingual POS tagging (English, Hindi, Marathi, Tamil, etc.) | POST | ๐ Check blog | Saket Pol | 2025-04-13 | โญโญ (Medium) | โ |
Project Title | Description | Code | Created | Completed |
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๐1-Generating QR Code in Python | Python,qrcode | Saad Abbasi | โ | |
๐1-Important Python Script | Python,qrcode | Saad Abbasi | โ |
Project Title | Datasets | Code |
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1-Building education chatbot for decreasing instructor workload in e-learning system | Dataset |
f1 | precision | recall | accuracy | training_time | inference_time | |
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NB | 0.830188679245283 | 0.8461538461538461 | 0.8148148148148148 | 0.8085106382978723 | 0.0032272338867187 | 0.0007801055908203 |
LR | 0.8518518518518519 | 0.8846153846153846 | 0.8214285714285714 | 0.8297872340425532 | 0.0356471538543701 | 0.0002150535583496 |
KNN | 0.7058823529411765 | 0.6923076923076923 | 0.72 | 0.6808510638297872 | 0.0005688667297363 | 0.0972669124603271 |
SVM | 0.8518518518518519 | 0.8846153846153846 | 0.8214285714285714 | 0.8297872340425532 | 0.0274648666381835 | 0.0030479431152343 |
XGBoost | 0.9122807017543859 | 1.0 | 0.8387096774193549 | 0.8936170212765957 | 0.241973876953125 | 0.0040738582611083984 |
RoBERTa | 0.9230769230769231 | 0.9230769230769231 | 0.9230769230769231 | 0.9148936170212766 | 24968.250607967377 | 68.44634509086609 |
- ๐ข Start with ML Regression โ Classification โ Clustering
- ๐ก Move to Deep Learning and Computer Vision
- ๐ด Advance into NLP, Transformers, and Research Projects
##Alogrithems - DL0101EN-3-1-Regression-with-Keras-py-v1.0.ipynb - DL0101EN-3-2-Classification-with-Keras-py-v1.0.ipynb - Keras - Tutorial - Happy House v1.ipynb - Keras_for_Beginners_Implementing_a_Convolutional_Neural_Network - Keras_for_Beginners_Building_Your_First_Neural_Network.ipynb
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Machine Learning 2. Movie_Recommender_9_26_2020.ipynb 3. Predict_IPL_Winner_with_ML.ipynb 4. Credit_Card_Fraud_Detection_DT_and_RF.ipynb 5. President_Heights_exploratory_data.ipynb 6. Birth Rate Analysis 7. Data Science Project on Area and Population 8. How to Save a Machine Learning Model? 9. Hate Speech Detection with Machine Learning
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Natural Language Processing 2. Next_Word_Prediction 3. Summarize_Text_with_Machine_Learning 4. Chatbot_using_Python.ipynb 5. Text_Classification 6. End-to-End Spam Detection with Python 7. Fake_News_Classifier_using_Bidirectional_LSTM.ipynb
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Project Need to Implement
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How to Detect Passive and Active Voice in Your Writing Using an LSTM
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UBER RIDES PREDICTION USING MACHINE LEARNING | Complete Project
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Predict Ads Click โ Practice Data Analysis and Logistic Regression Prediction
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Data Science Real-World Use Cases - Hands On PythonYour progress
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Predict The Future Price of Etherium Using Python & Machine Learning
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Machine Learning project : Cricket Score prediction using Python
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Machine Learning Projects | using python | with code | for college students
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Face Mask Detection using Python, Keras, OpenCV and MobileNet | Detect masks real-time video streams
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10 Best Data Science Projects to Get Hired and You Must Know in 2021
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Wine Recommender System Using Principal Component Analysis- Python
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Deep Learning Algorithms For Solving Advanced Mathematical Problems
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Video to Text Description Using Deep Learning and Transformers | COOT
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Forecasting the power generated by a solar plant using Neural Designer
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https://www.neuraldesigner.com/learning/examples/solar-power-generation
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How I Built and Deployed a Fun Serverless Machine Learning App
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20 Machine Learning Projects on Future Prediction with Python
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Data Science Project on Youtube Trending Videos Analysis with Python
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500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code
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Build a Personal AI Trainer| OpenCV Python 2021 | Computer Vision
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Smart Attendance Management System Based On Face Recognition
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Face Recognition Authentication in Flutter using TensorFlow & Firebase ML
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Face Recognition Authentication in Flutter using TensorFlow & Firebase ML
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Machine learning project| | Student exam mark prediction using python|
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Machine Learning Tutorial with Turi Create and Python (Diabetes Risk Prediction)
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Machine Learning Project : Weather prediction using Python ( Naรฏve Bayes )
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Build a Grammar Correction Python App with Gramformer and Gradio
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YouTube Recommendation System โ Machine Learning Project with Source Code
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Important Website For Projects
- dataspoof
- blobcity
- data-flair.training
- ai-techsystems
- Data Science Tutorial
- Data Science Tutorial
- Top 10 most promising AI
- Graph Algorithms
- Murtaza's Workshop - Robotics and AI
- projectsbasedlearning
- laconicml
- Machine Learning Hub
- techprofree
- Mathematics behind Data Science
- Machine Learning Projects
- 7 Computer Vision Projects for All Levels
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Make changes to the cloned repository
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Make sure you do not copy codes from external sources because that work will not be considered. Plagiarism is strictly not allowed.
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You can only work on issues that have been assigned to you.
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If you want to contribute the algorithm, it's preferrable that you create a new issue before making a PR and link your PR to that issue.
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If you have modified/added code work, make sure the code compiles before submitting.
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Strictly use snake_case (underscore_separated) in your file_name and push it in correct folder.
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Do not update the README.md.
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