You will get Predictive Data Analytics, Time Series Forecasting | ML Machine Learning
Project details
š Turn your data into future insights with Predictive Analytics & Time Series ML.
I specialize in building machine learning models that forecast trends, demand, sales, financials, and business KPIs. Using Python, scikit-learn, XGBoost, TensorFlow, Prophet, and ARIMA/LSTM, I desing ETL pipelines that help organizations make data-driven decisions with confidence.
š¹ What I Offer:
Predictive Modeling ā regression, classification, customer behavior prediction
Time Series Forecasting ā ARIMA, Prophet, LSTM, Transformers
Business Analytics ā demand, sales, finance, churn, revenue forecasting
Feature Engineering & Data Cleaning ā turning raw data into usable insights
Visualization ā Power BI, Tableau, Plotly
Deployment ā API FastAPI, Streamlit, Flask
š¹ Use Cases:
āļø Retail demand & sales prediction
āļø Financial market & price forecasting
āļø Energy consumption forecasting
āļø Supply chain optimization
āļø Customer churn prediction
āļø Healthcare & resource demand forecasting
š¹ Why Me?
5+ years in ML, Data Science & Forecasting
Classic Deep learning models
Delivered predictive solutions for banking, retail, and enterprise clients
Clear insights + production-ready deployment
I specialize in building machine learning models that forecast trends, demand, sales, financials, and business KPIs. Using Python, scikit-learn, XGBoost, TensorFlow, Prophet, and ARIMA/LSTM, I desing ETL pipelines that help organizations make data-driven decisions with confidence.
š¹ What I Offer:
Predictive Modeling ā regression, classification, customer behavior prediction
Time Series Forecasting ā ARIMA, Prophet, LSTM, Transformers
Business Analytics ā demand, sales, finance, churn, revenue forecasting
Feature Engineering & Data Cleaning ā turning raw data into usable insights
Visualization ā Power BI, Tableau, Plotly
Deployment ā API FastAPI, Streamlit, Flask
š¹ Use Cases:
āļø Retail demand & sales prediction
āļø Financial market & price forecasting
āļø Energy consumption forecasting
āļø Supply chain optimization
āļø Customer churn prediction
āļø Healthcare & resource demand forecasting
š¹ Why Me?
5+ years in ML, Data Science & Forecasting
Classic Deep learning models
Delivered predictive solutions for banking, retail, and enterprise clients
Clear insights + production-ready deployment
Programming Languages
HTML & CSS, JavaScript, PythonCoding Expertise
Performance Optimization, Security, DesignWhat's included
| Service Tiers |
Starter
$95
|
Standard
$750
|
Advanced
$1,495
|
|---|---|---|---|
| Delivery Time | 1 day | 3 days | 5 days |
Number of Revisions | Unlimited | Unlimited | Unlimited |
Number of Pages Mined/Scraped | 1 | 5 | 10 |
Number of Sources Mined/Scraped | 1 | 5 | 10 |
Install Script | |||
Test Script | - | ||
Task Automation | - | - |
Frequently asked questions
About Muhammad Noman
Python Data Scientist, ML & Big Data Engineer, Generative AI -LLM, API
Karachi, PakistanĀ - 10:17 am local time
I help enterprises transform raw data into scalable AI/ML solutions that cut costs, boost efficiency, and drive measurable ROI.
š¼ Work:
ā AI Agents & Chatbots: Built IBM Watson + LLM (LangChain, RAG, XAI) chatbot handling 5,000+ monthly queries, cutting response time by 40% and boosting CSAT by 18%
ā Fraud Detection Models: Developed an ML pipeline improving transaction monitoring by 20% accuracy and reducing false positives by 15%
ā OCR & Automation: Engineered OCR workflow with Python/OpenCV, integrated into Temenos T24, reducing manual data entry by 60%
ā Data Pipelines: Automated ETL (DB2 ā Hive ā SQL Server ā Power BI Server) via PySpark/Scala + Cron, reducing runtimes by 30% and ensuring reliability with log monitoring
ā Big Data Engineering: Managed 12-node Cloudera clusters (100+ TB) with 99.9% uptime, optimizing Spark + Hive workloads for faster queries
ā BI Dashboards: Designed 30+ dashboards in Power BI, Tableau, Qlik & IBM Cognos, deployed for 1,000+ enterprise users across Risk, Compliance & Finance
ā Streaming Pipelines: Built Kafka + Spark streaming systems for real-time analytics, processing 2M+ daily transactions
ā Regulatory Reporting: Automated SBP compliance reports (Python + SQL chaining), cutting manual effort by 70%
ā RPA Bots: Built a Selenium-based compliance bot, saving 50+ hours/month in analyst workload
ā Data Warehousing: Migrated 50+ TB structured/unstructured data on Cloudera stack (Hive, HDFS, Impala), cutting storage costs by 20%
š» Skills:
ā Languages: Python, R, Scala, SQL, Bash
ā Generative AI: LLMs (GPT, LLaMA, Claude), LLM fine-tuning (LoRA, PEFT), RAG pipelines, LangChain, LlamaIndex, AI Agents, Vector Databases (Pinecone, Weaviate, FAISS, Milvus, ChromaDB), Prompt Engineering, Chatbots, Multi-Modal AI, Knowledge Graphs, Guardrails, XAI (SHAP, LIME)
ā Big Data & Cloud: Cloudera, Hadoop (HDFS, MapReduce, YARN), Spark (PySpark/Scala, MLlib, Streaming), Kafka, Flink, Hive, Pig, Impala, Storm, Sqoop, Oozie, NiFi, Zookeeper, Databricks, Snowflake, Delta Lake, Data Warehouse Architecture, Presto, AWS (SageMaker, EMR, S3, Lambda, Redshift), GCP (BigQuery, Vertex AI), Azure (Synapse, ML, OpenAI)
ā ETL & Data Engineering: Airflow, dbt, Cron, Pandas, NumPy, Spark SQL, Data Wrangling, APIs, Automation, ETL pipelines, OpenCV, BeautifulSoup, Scrapy
ā Databases: SQL Server, MySQL, PostgreSQL, IBM DB2, MongoDB, Hive, Cassandra, Redis, Elasticsearch
ā Machine Learning & Data Science: Predictive analytics (Deposit Prediction, Fraud Detection), NLP, Computer Vision, OCR, Supervised/Unsupervised Learning, Reinforcement Learning, Deep Learning (CNNs, RNNs, Transformers), scikit-learn, TensorFlow, Keras, PyTorch, XGBoost, LightGBM, CatBoost, Hugging Face, AutoML, MLOps (MLflow, Kubeflow, DVC, Airflow
ā Business Intelligence & Visualization: Power BI, Tableau, Looker, Qlik, IBM Cognos Analytics, Excel, Matplotlib, Seaborn, Plotly, PBI Report Server Configuration
ā Development (Backend & Full-Stack): Python (APIs, automation, ETL, backend), Django, Flask, FastAPI, Streamlit, Node.js, React, WordPress (Elementor), Odoo ERP, AI SaaS apps
ā Automation: RPA bots (Selenium), Web Scraping, ETL Workflow Automation
ā DevOps & Tools: Git, Gitlab, Docker, Kubernetes, CI/CD pipelines, Jupyter, PyCharm, Anaconda Distribution
š Trusted by clients in banking, fintech, e-commerce, and enterprise systems for writing clean, scalable, and production-ready code.
š© Not sure where to start? Share your challenge with me, and Iāll map out a step-by-step AI/data strategy - no fluff, just actionable insights that you can apply right away.
Steps for completing your project
After purchasing the project, send requirements so Muhammad Noman can start the project.
Delivery time starts when Muhammad Noman receives requirements from you.
Muhammad Noman works on your project following the steps below.
Revisions may occur after the delivery date.
Whatās your business goal (sales, demand, finance, etc.)?
Do you have a dataset? If yes, share format & sample.