You will get complete machine learning project in python
Rising Talent
Rising Talent
Project details
Machine learning project in Python:
Collect and preprocess the data: This includes gathering the data, cleaning it, and formatting it in a way that can be used for analysis and modeling.
Explore and analyze the data: This involves using visualizations and statistical analysis to understand the characteristics of the data and any patterns that might exist.
Select and train a model: This involves selecting a machine learning algorithm and training it on the data. There may be several steps involved in this process, such as selecting the appropriate hyperparameters and evaluating the model's performance.
Evaluate the model: Once the model has been trained, it is important to evaluate its performance on unseen data to see how well it generalizes. This can be done through techniques such as cross-validation or using a hold-out test set.
Deploy the model: If the model is performing well and has met the project goals, it can be deployed in a production environment where it can be used to make predictions on new data.
Throughout this process, it is important to keep a clear record of the steps taken and the decisions made, as well as any challenges encountered and how they were addressed.
Collect and preprocess the data: This includes gathering the data, cleaning it, and formatting it in a way that can be used for analysis and modeling.
Explore and analyze the data: This involves using visualizations and statistical analysis to understand the characteristics of the data and any patterns that might exist.
Select and train a model: This involves selecting a machine learning algorithm and training it on the data. There may be several steps involved in this process, such as selecting the appropriate hyperparameters and evaluating the model's performance.
Evaluate the model: Once the model has been trained, it is important to evaluate its performance on unseen data to see how well it generalizes. This can be done through techniques such as cross-validation or using a hold-out test set.
Deploy the model: If the model is performing well and has met the project goals, it can be deployed in a production environment where it can be used to make predictions on new data.
Throughout this process, it is important to keep a clear record of the steps taken and the decisions made, as well as any challenges encountered and how they were addressed.
Machine Learning Tools
Azure Machine Learning, ChatGPT, GPT-3, Keras, Microsoft Excel, Microsoft Power BI, NLTK, NumPy, OpenCV, pandas, Python, Python Scikit-Learn, RapidMiner, scikit-learn, SQL, Tableau, TensorFlow, XGBoostWhat's included $15
These options are included with the project scope.
$15
- Delivery Time 1 day
- Number of Revisions 2
- Number of Model Variations 1
- Number of Scenarios 1
- Number of Graphs/Charts 3
- Model Validation/Testing
- Model Documentation
- Data Source Connectivity
- Source Code
3 reviews
(3)
(0)
(0)
(0)
(0)
This project doesn't have any reviews.
AS
Armando S.
Dec 19, 2025
n8n Automation & API Integration Specialist
Highly recommend! Muhammad, crushed the n8n automation project, designing seamless API-driven workflows that boosted our efficiency. Super responsive, detail-oriented, and a pro at integrating third-party services. Delivered top-notch work and collaborated brilliantly! Would definitely hire again
WA
Wajid A.
Mar 2, 2024
Need ML Models and Data Processing expert
Working with Hassan was an exceptional experience. Their expertise in machine learning surpassed my expectations. They not only delivered high-quality results but also provided insightful suggestions to improve our project. Communication was seamless, deadlines were met, and the final outcome exceeded our goals. I highly recommend [Your Name] for any machine learning projects.
WA
Wajid A.
Dec 28, 2022
Need a Python Developer (Machine Learning)
"Very good to work with. Has good knowledge of ML, AI. Always answered my questions with patience and replied ontime. Please to work with and will rehire in future"
About Muhammad
AI Engineer | RAG, LLMs, AI Agents, Automation, End-to-End Development
Islamabad, Pakistan - 3:52 am local time
I help businesses build production-ready AI products from end to end.
I’m Muhammad Hassan, an AI Engineer specializing in RAG systems, LLM applications, AI agents, document intelligence, backend development, and workflow automation. I build complete solutions that move beyond prototypes: systems that retrieve the right information, generate reliable outputs, connect with existing tools, and fit into real business operations.
What I can help you build
RAG chatbots and knowledge assistants
I design end-to-end retrieval systems with document ingestion, chunking, embeddings, hybrid search, reranking, memory, and source-grounded responses.
LLM-powered applications
I build AI features and full applications for support, research, reporting, internal operations, and domain-specific workflows.
Document intelligence pipelines
I turn PDFs, scanned files, tables, reports, and other unstructured documents into structured, searchable, usable data.
AI agents and workflow automation
I create agentic workflows and automations using APIs, webhooks, and tools like n8n to reduce manual work and improve operational efficiency.
Backend and product development
I build the infrastructure behind AI products: Python services, FastAPI backends, vector database integrations, SQL pipelines, and deployment-ready APIs.
Tech stack
Python, FastAPI, LangChain, OpenAI, Claude, Llama, Mistral, Pinecone, Weaviate, ChromaDB, Supabase, SQL, ClickHouse, OCR, document parsing, API integrations, and n8n.
How I work
I approach every project like a product, not a one-off task. That means:
clear architecture
reliable retrieval and outputs
maintainable code
scalable design
practical business value
If you need a developer who can build the AI layer, backend layer, and automation layer into one complete solution, I’d be glad to help.
Steps for completing your project
After purchasing the project, send requirements so Muhammad can start the project.
Delivery time starts when Muhammad receives requirements from you.
Muhammad works on your project following the steps below.
Revisions may occur after the delivery date.
First Milestone