You will get Custom AI Predictive Analytics & Forecasting System
Project details
Get a custom AI predictive analytics and forecasting solution designed around your business data and prediction goals. I can build machine learning models for sales, revenue, demand, customer behavior, churn, KPIs, and other forecasting use cases. The workflow includes data preprocessing, feature engineering, model development, validation, performance analysis, forecasting, and professional visualization. Depending on the selected package, you can receive source code, model documentation, data connectivity, dashboards, and API-ready components. The goal is to turn historical data into reliable predictions and actionable business insights using Python and modern machine learning techniques.
Machine Learning Tools
Microsoft Power BI, MLflow, NumPy, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, SQL, Tableau, TensorFlow, XGBoostWhat's included
| Service Tiers |
Starter
$50
|
Standard
$150
|
Advanced
$250
|
|---|---|---|---|
| Delivery Time | 4 days | 7 days | 8 days |
Number of Revisions | 1 | 2 | 4 |
Number of Model Variations | 1 | 2 | 4 |
Number of Scenarios | 1 | 3 | 5 |
Number of Graphs/Charts | 3 | 5 | 5 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | - | ||
Source Code |
Frequently asked questions
About M Asad
Machine Learning Engineer | AI, LLM, RAG & Computer Vision
Lahore, Pakistan - 8:33 am local time
I’m a Machine Learning Engineer and Python Developer specializing in building practical AI and machine learning solutions from model development to API and application integration.
My core expertise includes:
• Machine Learning & Deep Learning
• Python, TensorFlow, Keras & Scikit-Learn
• LLM Applications, RAG & AI Agents
• LangChain & LangGraph
• Vector Databases — FAISS, Chroma & Qdrant
• NLP & AI Chatbots
• Computer Vision, OpenCV & YOLO
• FastAPI & REST APIs
• Predictive Analytics & Data Analysis
• React, Streamlit, Docker & Git/GitHub
I have professional experience designing and deploying ML services across NLP, computer vision, and predictive analytics. I’ve also built FastAPI-based REST APIs for ML models and integrated AI features into web applications.
My project experience includes an LLM-powered RAG assistant with agentic workflows, an agriculture AI assistant with English/Urdu chatbot support, a multimodal emotion-based recommendation system, a real-time fire detection system, and a YOLO-based object detection application.
I focus on building solutions that are practical, reliable, and ready to move beyond a basic prototype.
If you need help with an AI/ML model, RAG application, AI agent, computer vision system, predictive analytics solution, or FastAPI ML backend, I’d be happy to help.
Let’s turn your AI idea into a working solution.
Steps for completing your project
After purchasing the project, send requirements so M Asad can start the project.
Delivery time starts when M Asad receives requirements from you.
M Asad works on your project following the steps below.
Revisions may occur after the delivery date.
Data Analysis & Preparation
Review the provided dataset, identify relevant features, clean the data, and prepare it for machine learning.
Feature Engineering
Transform the available data into meaningful features suitable for prediction and forecasting.