You will get a end to end machine learning and deep learning model
Project details
You will get a complete end-to-end Machine Learning and Deep Learning solution, built with industry-standard tools such as Scikit-Learn, TensorFlow, PyTorch, XGBoost, Pandas, and Streamlit. I provide clean data pipelines, powerful predictive models, professional reports, and an optional interactive web app for deployment.
With strong expertise in Data Science and AI development, I focus on creating accurate, fast, and production-ready ML systems tailored to your exact business needs. Whether you need classification, regression, image recognition, NLP, or advanced neural networks — I deliver models that are optimized, well-documented, and easy to use. The work you receive will be high-quality, customizable, and ready for real-world use.
This project delivers a full professional Machine Learning + Deep Learning pipeline:
• Data cleaning and preprocessing
• Advanced exploratory data analysis with graphs
• Multiple ML/DL models (Random Forest, XGBoost, CNNs, MLP, etc.)
• Hyperparameter tuning
• Model comparison and selection
• Professional PDF report with charts
• Well-documented Jupyter notebook
• Optional Streamlit prediction app
• Fully reproducible code and requirements
With strong expertise in Data Science and AI development, I focus on creating accurate, fast, and production-ready ML systems tailored to your exact business needs. Whether you need classification, regression, image recognition, NLP, or advanced neural networks — I deliver models that are optimized, well-documented, and easy to use. The work you receive will be high-quality, customizable, and ready for real-world use.
This project delivers a full professional Machine Learning + Deep Learning pipeline:
• Data cleaning and preprocessing
• Advanced exploratory data analysis with graphs
• Multiple ML/DL models (Random Forest, XGBoost, CNNs, MLP, etc.)
• Hyperparameter tuning
• Model comparison and selection
• Professional PDF report with charts
• Well-documented Jupyter notebook
• Optional Streamlit prediction app
• Fully reproducible code and requirements
Machine Learning Tools
Azure Machine Learning, BERT, ChatGPT, Deeplearning4j, GitHub Copilot, Google AutoML, GPT-3, MLflow, NLTK, NumPy, NVIDIA AI Platform, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, Sonnet, SQL, Stanford CoreNLP, TensorFlow, TextBlob, Vertex AI, Word2vec, XGBoostWhat's included
| Service Tiers |
Starter
$70
|
Standard
$160
|
Advanced
$290
|
|---|---|---|---|
| Delivery Time | 5 days | 13 days | 25 days |
Number of Revisions | 0 | 1 | 2 |
Number of Model Variations | 1 | 3 | 5 |
Number of Scenarios | 1 | 1 | 1 |
Number of Graphs/Charts | 3 | 5 | 7 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | - | ||
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$30 - $50
Additional Revision
+$25
Additional Model Variation
(+ 3 Days)
+$40
Additional Scenario
(+ 5 Days)
+$80
Additional Graph/Chart
(+ 1 Day)
+$15
Data Source Connectivity
(+ 4 Days)
+$70Frequently asked questions
About Muhammad Sahil
Jr. Data Scientist with expertise in ML, AI Automation, and Agentic AI
Mirpur Mathelo, Pakistan - 11:30 pm local time
What I deliver (concise & actionable)
• Reproducible data pipelines (pandas, SQL) with robust missing-value handling, outlier treatment, scaling and feature engineering.
• Clear EDA and stakeholder-ready visualizations (interactive where needed) so non-technical teams can act.
• End-to-end ML/DL solutions: model selection, cross-validation, hyperparameter tuning, and explainability (feature importance / SHAP).
• NLP & RAG systems: text preprocessing, embeddings, semantic search, and conversational QA over documents.
• Chatbots & automation: intent detection, dialogue flows, webhook/CRM integration, and lightweight demos.
• Deployment-ready artifacts: well-documented notebooks, `requirements.txt`, demo apps (Streamlit/Flask) and code organized for containerization or API deployment.
Tools & best practices:
Python, pandas, scikit-learn, XGBoost / LightGBM, TensorFlow / PyTorch, Hugging Face tooling, LangChain-style RAG patterns, Streamlit, Flask, and SQL — plus clear documentation and version-friendly code.
Why hire me:
I combine an agency mindset with hands-on technical skills — producing client-ready deliverables, measurable outcomes, and clear communication. I’ll audit your data, propose a focused pipeline, and deliver a prototype or production-ready model depending on your needs.
Steps for completing your project
After purchasing the project, send requirements so Muhammad Sahil can start the project.
Delivery time starts when Muhammad Sahil receives requirements from you.
Muhammad Sahil works on your project following the steps below.
Revisions may occur after the delivery date.
Project Requirements & Dataset Submission
Client sends dataset (CSV/Excel/SQL) and describes the goal of the project.
Data Cleaning & Exploratory Analysis
I analyze the dataset, handle missing values, outliers, encode features, and create detailed visualizations.