You will get Data Science & Machine Learning with Python – Classification, Regression
Rising Talent
Rising Talent
Project details
Get a clean, production-ready Data Science & Machine Learning workflow in Python for classification, regression, or deep EDA. I turn messy data into accurate, explainable models and clear business insights.
What you get
Data audit, cleaning, and feature engineering
EDA visuals (distributions, correlations, outliers)
Baseline + tuned models (scikit-learn/XGBoost/TensorFlow)
Cross-validation and clear metrics (Accuracy/F1/MAE)
Feature importance and recommendations
Well-structured notebook/script, charts, and short report
Why me
3+ years hands-on experience
Delivered projects: sentiment analysis (NLP), disease risk analytics, house price prediction
Fast, friendly communication and on-time delivery
Google-certified; clean, reproducible code
Process
Discover goals → Data audit → EDA → Model training & tuning → Evaluation → Delivery.
Extras: API/dashboard handoff and ongoing support. Let’s discuss your target variable and success metric so I can propose the best approach.
What you get
Data audit, cleaning, and feature engineering
EDA visuals (distributions, correlations, outliers)
Baseline + tuned models (scikit-learn/XGBoost/TensorFlow)
Cross-validation and clear metrics (Accuracy/F1/MAE)
Feature importance and recommendations
Well-structured notebook/script, charts, and short report
Why me
3+ years hands-on experience
Delivered projects: sentiment analysis (NLP), disease risk analytics, house price prediction
Fast, friendly communication and on-time delivery
Google-certified; clean, reproducible code
Process
Discover goals → Data audit → EDA → Model training & tuning → Evaluation → Delivery.
Extras: API/dashboard handoff and ongoing support. Let’s discuss your target variable and success metric so I can propose the best approach.
Machine Learning Tools
Keras, MATLAB, NumPy, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, SQL, TensorFlow, XGBoostWhat's included
| Service Tiers |
Starter
$45
|
Standard
$85
|
Advanced
$170
|
|---|---|---|---|
| Delivery Time | 2 days | 3 days | 5 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 3 |
Number of Graphs/Charts | 1 | 3 | 0 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code |
Frequently asked questions
About Hamza
Machine Learning & Data Science Expert
Faisalabad, Pakistan - 2:21 pm local time
🔥𝐒𝐭𝐮𝐜𝐤 𝐰𝐢𝐭𝐡 𝐬𝐭𝐚𝐠𝐧𝐚𝐧𝐭 𝐚𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬? 𝐘𝐨𝐮𝐫 𝐜𝐨𝐦𝐩𝐞𝐭𝐢𝐭𝐨𝐫𝐬 𝐚𝐫𝐞 𝐚𝐥𝐫𝐞𝐚𝐝𝐲 𝐮𝐬𝐢𝐧𝐠 𝐀𝐈 𝐭𝐨 𝐩𝐫𝐞𝐝𝐢𝐜𝐭 𝐭𝐫𝐞𝐧𝐝𝐬 𝐲𝐨𝐮 𝐜𝐚𝐧’𝐭 𝐬𝐞𝐞.
I design 𝐚𝐝𝐚𝐩𝐭𝐢𝐯𝐞 𝐦𝐚𝐜𝐡𝐢𝐧𝐞 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 that outpace the market—so you’re always two steps ahead.
2+ years of hands-on expertise in:
🚀 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴: Predictive models for revenue growth & risk mitigation.
👁️ 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗩𝗶𝘀𝗶𝗼𝗻: Real-time object detection, medical imaging, and AR solutions.
📊 𝗣𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝘃𝗲 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀: Time-series forecasting, anomaly detection, and root cause analysis.
🚨 𝐖𝐡𝐲 𝐂𝐥𝐢𝐞𝐧𝐭𝐬 𝐇𝐢𝐫𝐞 𝐌𝐞:
✅ Full-Time Freelancer | 50+ hrs/week | Time Zone Agnostic
✅ End-to-End Ownership: From raw data to 99.9% uptime production systems.
✅ No More “Lab-to-Production Gaps”: My models work where it matters—your real-world environment.
💡 Core Innovations
🚀 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 & 𝗗𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴
🔍 𝗙𝗿𝗮𝘂𝗱 𝗱𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 reducing losses by 62% for fintech.
⚡ 𝗛𝗶𝗴𝗵-𝗳𝗿𝗲𝗾𝘂𝗲𝗻𝗰𝘆 𝘁𝗿𝗮𝗱𝗶𝗻𝗴 with microsecond latency.
👁️ 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗩𝗶𝘀𝗶𝗼𝗻
📹 𝗥𝗲𝗮𝗹-𝘁𝗶𝗺𝗲 𝘀𝘂𝗿𝘃𝗲𝗶𝗹𝗹𝗮𝗻𝗰𝗲 with 99.5% accuracy.
🩺 𝗠𝗲𝗱𝗶𝗰𝗮𝗹 𝗶𝗺𝗮𝗴𝗶𝗻𝗴 with 95%+ sensitivity.
🤖 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 & 𝗟𝗟𝗠𝘀
💬 𝗖𝘂𝘀𝘁𝗼𝗺 𝗖𝗵𝗮𝘁𝗚𝗣𝗧 for enterprise knowledge bases.
🎙️ 𝗠𝘂𝗹𝘁𝗶𝗹𝗶𝗻𝗴𝘂𝗮𝗹 𝘃𝗼𝗶𝗰𝗲 cloning for global support.
📊 𝗣𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝘃𝗲 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀
📦 𝗗𝗲𝗺𝗮𝗻𝗱 𝗳𝗼𝗿𝗲𝗰𝗮𝘀𝘁𝗶𝗻𝗴 cutting inventory costs by 30%.
⚠️ 𝗔𝗻𝗼𝗺𝗮𝗹𝘆 𝗱𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 preventing $2M+ in downtime.
🛠️ 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗔𝗿𝘀𝗲𝗻𝗮𝗹
🚀 𝗔𝗜 & 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀
PyTorch, TensorFlow, Keras, JAX, HuggingFace Transformers, FastAI
Scikit-Learn, XGBoost, LightGBM, CatBoost
ONNX, TensorRT, OpenVINO, DeepSpeed
☁️ 𝗖𝗹𝗼𝘂𝗱 & 𝗠𝗟𝗢𝗽𝘀
AWS (SageMaker, Lambda, Bedrock, S3, EC2, Fargate, Step Functions)
Google Cloud (Vertex AI, BigQuery ML, AI Platform, Cloud Run)
Azure ML, Databricks, Snowflake, IBM Watson
Kubernetes, Docker, MLflow, Kubeflow, Airflow, Prefect, BentoML
🧠 𝗟𝗮𝗿𝗴𝗲 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗠𝗼𝗱𝗲𝗹𝘀 (𝗟𝗟𝗠𝘀) & 𝗡𝗟𝗣
GPT-4, LLaMA-2, Mistral, Falcon, Claude, Cohere, Anthropic, DeepSeek
Pinecone, FAISS, Weaviate, Qdrant, ChromaDB (Vector Search)
RAG Pipelines, Haystack, LangChain, AutoGPT, LLamaIndex
📊 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 & 𝗦𝘁𝗼𝗿𝗮𝗴𝗲
Apache Spark, Dask, Ray, Delta Lake
Apache Kafka, RabbitMQ, Redis, PostgreSQL, MongoDB, ClickHouse
Snowflake, BigQuery, Google DataFlow, AWS Redshift
🎨 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗩𝗶𝘀𝗶𝗼𝗻 & 𝗜𝗺𝗮𝗴𝗲 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴
OpenCV, Detectron2, MMDetection, YOLO, Mediapipe, torchvision
Tesseract OCR, PaddleOCR, CLIP, Stable Diffusion, SAM (Segment Anything Model)
📡 𝗘𝗱𝗴𝗲 𝗔𝗜 & 𝗠𝗼𝗱𝗲𝗹 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻
NVIDIA Jetson, Coral Edge TPU, TensorRT, OpenVINO, TFLite, CoreML
TVM, DeepSpeed, HuggingFace Optimum, Flash Attention
🔌 𝗔𝗣𝗜𝘀 & 𝗗𝗲𝘃 𝗧𝗼𝗼𝗹𝘀
OpenAI API, HuggingFace API, FastAPI, Flask, Django, Streamlit, Gradio
PyTorch Lightning, Triton Inference Server, DeepSpeed, TorchServe
⚡ 𝗛𝗶𝗴𝗵-𝗣𝗲𝗿𝗳𝗼𝗿𝗺𝗮𝗻𝗰𝗲 & 𝗗𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗲𝗱 𝗖𝗼𝗺𝗽𝘂𝘁𝗶𝗻𝗴
NVIDIA CUDA, cuDNN, ROCm (AMD), PyTorch Distributed, Horovod, MPI
TPUs (Google Cloud), Habana Gaudi, AWS Inferentia
🏆 Proven Impact
𝟰𝟬% 𝗙𝗮𝘀𝘁𝗲𝗿 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁: Pre-built pipelines for rapid scaling.
Steps for completing your project
After purchasing the project, send requirements so Hamza can start the project.
Delivery time starts when Hamza receives requirements from you.
Hamza works on your project following the steps below.
Revisions may occur after the delivery date.
Kickoff & scope confirmation
Clarify objective, target variable, metric, timeline, and deliverables. Verify data access and privacy. Agree on acceptance criteria.
Data audit & cleaning
Check missing values, duplicates, outliers, types. Fix issues, encode features, split train/test. Share a short data-quality note.