You will get a machine learning pipeline and insightful data analysis
Project details
You will get a custom end-to-end production-ready machine learning pipeline and data analysis for your project.
My tech stack:
Programming and Libraries:
Python (pandas, NumPy, scikit-learn, XGBoost, LightGBM, statsmodels)
Deep Learning (PyTorch, TensorFlow, DGL)
Visualization (matplotlib, Plotly, Dash, NetworkX)
Databases and Query Languages:
SQL (PostgreSQL, MySQL)
Graph Databases (ArangoDB)
My tech stack:
Programming and Libraries:
Python (pandas, NumPy, scikit-learn, XGBoost, LightGBM, statsmodels)
Deep Learning (PyTorch, TensorFlow, DGL)
Visualization (matplotlib, Plotly, Dash, NetworkX)
Databases and Query Languages:
SQL (PostgreSQL, MySQL)
Graph Databases (ArangoDB)
What's included
| Service Tiers |
Starter
$90
|
Standard
$200
|
Advanced
$500
|
|---|---|---|---|
| Delivery Time | 3 days | 7 days | 14 days |
Number of Revisions | 1 | 2 | 5 |
Number of Model Variations | 1 | 2 | 2 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | |||
Source Code |
About Vladislav
Data Scientist | Machine Learning Engineer | LLM Agents & RAG
Almaty, Kazakhstan - 9:31 pm local time
My past projects included:
Graph Databases and Analytics
Architected and populated a graph database for relationship analysis, collaborating with data engineers on data ingestion, cleaning, and schema design.
Created interactive visualizations to highlight key customer and transaction patterns.
Implemented graph machine learning models.
Anti-Fraud Modeling
Built a machine learning pipeline to score new clients in real time, incorporating graph-based features and model explainability.
Time-Series Forecasting and Sales Prediction
Designed a sales forecasting module that aggregated historical sales, promotions, holidays.
Integrated the model into the analytics infrastructure, enabling automated daily forecasts and dashboard updates for regional sales teams.
CRM Campaign Analytics
Performed data mining on marketing datasets to identify high-value segments.
Designed A/B tests and uplift models to measure campaign effectiveness.
Predictive Models for HR and Employee Retention
Developed a machine learning model to predict a churn-risk of employees.
Technical Skills
Programming and Libraries:
Machine learning and data science (pandas, NumPy, scikit-learn, XGBoost, LightGBM, statsmodels)
Deep Learning (PyTorch, TensorFlow, DGL)
Visualization (matplotlib, Plotly, Dash, NetworkX)
LLM Agents & RAG (LangGraph, LangChain, Transformers, Qdrant)
Deployment: Docker, Flask, AWS
Databases and Query Languages:
SQL (PostgreSQL, MySQL)
Graph Databases (ArangoDB)
Steps for completing your project
After purchasing the project, send requirements so Vladislav can start the project.
Delivery time starts when Vladislav receives requirements from you.
Vladislav works on your project following the steps below.
Revisions may occur after the delivery date.
Determining the scope of the project
MVP development