Female Safety Data & Modelling

@nrajuu07

As a highly experienced data scientist, I possess the necessary skills to drive this project to success. With a deep understanding in statistical and quantitative analysis, I'm well-equipped to gather, clean and document the datasets from GitHub, Kaggle and Mendeley Data as demanded. Utilizing powerful Python libraries such as pandas and scikit-learn, I'll build an effective analytics engine for your safety web-app. I've garnered comprehensive expertise in machine learning techniques including decision trees, random forests and support vector machines, which are perfect for your analytics needs. My thoroughness in reporting metrics such as Accuracy, Precision, Recall and F1-Score using stratified cross-validation ensures transparency and assists in determining the best model that'll integrate seamlessly into your pipeline.

@chraheelbhatti

As a seasoned Data Scientist and ML Engineer with hands-on expertise in Python, Data Science, and Data Visualization - your project aligns perfectly with my skill set and experience. Over the span of my 8-year career, I have successfully built and deployed accurate ML models for various clients including State Institutions and Banking institutions, solving issues ranging from automated traffic law enforcement to employee recognition. Furthermore, as a PhD researcher specialized in Machine Learning, trained at COMSATS University among other prestigious organizations, I promise clarity through reproducibility via well-commented code with concise readmes. By selecting me for this project, you gain not just my technical skills but my commitment to delivering quality research that truly serves your needs. Let's partner to build an app that puts female safety at the forefront by leveraging powerful ML algorithms!

@mouniir10

Hello, I’m a data scientist with extensive experience in Python, pandas, and scikit-learn. I have built 100+ models achieving 90%+ accuracy. I can provide clear, reproducible, app-ready code with performance metrics.

@Rashidminhas457

Hi I can curate reliable crime datasets (GitHub, Kaggle, Mendeley), clean them, and structure everything for direct use in your app. Each dataset will include a simple README for clarity. I’ll also build Python notebooks (pandas + scikit-learn) to train Decision Tree, Random Forest, and SVM models with stratified cross-validation, and provide a clear comparison (Accuracy, Precision, Recall, F1) with a final recommendation. Everything will be clean, reproducible, and ready to integrate. I have solid experience in Python, data analysis, and ML workflows. Thanks

@ayush01011

Hi, I’m very glad to see this project and interested to work with you, it matches to my skills and experiences, I’ve worked on many similar projects previously and have good working experience in this field, I’m sure, I can provide you the best outcome exactly as to your requirement, Please let me know about the project and let’s discuss something more about it, Call or WhatsApp me here (+91) 94543-89834 Thanking you.

@nisarg28

Hi, I can help you build a reliable dataset foundation and complete the end-to-end ML workflow for your safety web app. I will curate high-quality, publicly available tabular datasets related to crimes affecting women from GitHub, Kaggle, and Mendeley Data, along with optional relevant sources if needed. Each dataset will include original and cleaned versions, with clear documentation and READMEs. I’ll develop preprocessing and feature engineering pipelines, followed by training Decision Tree, Random Forest, and SVM models using pandas and scikit-learn. All models will be evaluated using stratified cross-validation with Accuracy, Precision, Recall, and F1-score. You’ll receive well-structured notebooks/scripts, a comparative metrics table, and a clear recommendation for the best model to integrate into your app. Ready to start and ensure clean, reproducible, production-ready work.

@Saikasbe7

Hello, Your project aligns well with my skills in Python, data analysis, and machine learning, and I’m confident I can deliver a clean, well-structured dataset-to-model pipeline as required. I will carefully curate relevant datasets from GitHub, Kaggle, and Mendeley Data, perform proper preprocessing and feature engineering, and implement Decision Tree, Random Forest, and SVM models with stratified cross-validation. All results will include Accuracy, Precision, Recall, and F1-score, along with a clear comparison and recommendation. I focus on writing well-documented, reproducible code so it can be directly integrated into your web application. As I am starting my freelance journey, I am highly motivated to deliver quality work and build long-term client relationships. I would really appreciate the opportunity to work on this project and prove my capability through results. I can complete this project within **4–5 days**, and I’m happy to share an early sample for your review. Looking forward to working with you. Thank you.

@Amisha571

Hi, This project fits well with my experience in building data pipelines, running ML experiments, and writing clean, reusable Python code. How I’ll approach it: Dataset Curation I’ll collect relevant crime datasets (like domestic violence, sexual assault, and harassment) from trusted sources such as GitHub, Kaggle, and Mendeley Data. Each dataset will include clear documentation on its source, usage, and key details. Pre-processing & Modeling I’ll clean and prepare the data using pandas, then train Decision Tree, Random Forest, and SVM models using scikit-learn. Performance will be evaluated using Accuracy, Precision, Recall, and F1-score with proper cross-validation. What you’ll receive: → Well-organized datasets (raw + cleaned) with documentation → A clear preprocessing and feature engineering notebook → Three easy-to-use, well-commented training notebooks → A comparison of model performance with a final recommendation Everything will be structured so your team can easily use and build on it. Happy to share samples or discuss further.

@AtharvMore

Hello, I’m excited to bid on your project for a reliable analytics engine in your women’s safety web-app. I’ve previously worked with NCRB-based crimes-against-women datasets across multiple projects (analysis, visualization, predictive modeling). I already have cleaned and raw versions ready, so I can quickly refresh, merge, and move directly into preprocessing and modeling. I’ll use trusted open datasets: Kaggle (2001–2021): state-wise NCRB data (rape, kidnapping, dowry deaths, etc.) Kaggle (2022): latest update for better trend accuracy Mendeley (2001–2022): longitudinal data for validation All are openly licensed with attribution. Deliverables: Clean, modular, well-documented code To align: Target task? (risk classification, prediction, hotspot scoring) Feature priorities? Deadline? Since data is ready, I can deliver quickly. Happy to discuss details on a quick call. Best regards, Atharv

@haoz21

I am well-qualified for this work, holding a strong academic background in mathematics and extensive hands-on experience in data science. In my wireless communication link rate modeling project, I applied a Random Forest algorithm for modeling and won the Second Prize in the "Huawei Cup" 22nd China Graduate Mathematical Modeling Competition. This experience showcases my ability to handle data preparation, implement machine learning models, evaluate results, and communicate insights effectively—skills that are essential for delivering the datasets, preprocessing scripts, model training notebooks, and clear recommendations required for your safety web-app. I consistently write clean, reproducible, and well-commented code, ensuring smooth integration into production applications.