You will get a Custom Machine Learning model | XGBoost | TensorFlow | Python
Project details
Looking for a professional Data Scientist to solve real-world problems with machine learning? This project offers a complete data science solution - from raw data analysis to model deployment. I use Python, scikit-learn, TensorFlow, and Pandas to build high-performance machine learning models tailored to your goals.
Whether you need a classification model, regression analysis, NLP pipeline, or forecasting system, I’ll handle every step: data cleaning, feature engineering, model training, hyperparameter tuning, and evaluation. You'll receive well-documented Python code, visual reports, and optional deployment via REST API or Docker.
This service is ideal for businesses and teams that need clear, actionable insights and production-ready data science workflows. Let’s turn your data into decisions with clean code, strong models, and expert-level machine learning practices.
Whether you need a classification model, regression analysis, NLP pipeline, or forecasting system, I’ll handle every step: data cleaning, feature engineering, model training, hyperparameter tuning, and evaluation. You'll receive well-documented Python code, visual reports, and optional deployment via REST API or Docker.
This service is ideal for businesses and teams that need clear, actionable insights and production-ready data science workflows. Let’s turn your data into decisions with clean code, strong models, and expert-level machine learning practices.
Machine Learning Tools
Amazon SageMaker, Apache Spark, Apache Spark MLlib, BERT, Databricks Platform, Databricks MLflow, GitHub Copilot, Google AutoML, Keras, Microsoft Excel, Microsoft Power BI, MLflow, NumPy, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, Scrapy, Sonnet, SQL, TensorFlow, XGBoostWhat's included $10,000
These options are included with the project scope.
$10,000
- Delivery Time 60 days
- Number of Revisions 1
- Number of Model Variations 2
- Number of Scenarios 2
- Number of Graphs/Charts 3
- Model Validation/Testing
- Model Documentation
- Data Source Connectivity
- Source Code
Optional add-ons
You can add these on the next page.
Fast 30 Days Delivery
+$4,000
Additional Revision
+$1,000
Additional Model Variation
(+ 2 Days)
+$1,000
Additional Scenario
(+ 1 Day)
+$1,000
Additional Graph/Chart
(+ 1 Day)
+$1,000About Vladyslav
Machine Learning | Data Scientist | AI Engineer | Data Analysis | LLM
Lodz, Poland - 11:04 pm local time
Hi, I'm Vlad Didukh - Machine Learning Engineer, AI Engineer, and Data Scientist with 8+ years delivering practical AI solutions that increase revenue and reduce costs through measurable results.
As founder of Dastellar, data-driven solutions company, I've led Data Science, Machine Learning and Generative AI projects for 50+ clients across various industries. This gives me unique insight into both technical execution and business strategy.
🎯 Recent Client Results
- 30% reduction in out-of-stock events through Machine Learning demand forecasting
- 34% improvement in forecast accuracy for inventory management
- 28% decrease in operational time via AI-powered assistants
- 47% faster ML anomaly detection in sensor systems
- 22% reduction in overstocking through intelligent Machine Learning optimization
📊 Industry Success Stories
- E-commerce: Created customer lifetime value segmentation model which helped increase email ROI on high CLV customers by 84%, drop CAC by 38% and increase LTV by 25%.
- Manufacturing: Built predictive maintenance system reducing equipment downtime by 25% and cutting maintenance costs by 20%.
- Energy & Utilities: Deployed demand forecasting model improving grid efficiency by 22% and reducing energy waste.
🔧 Core Expertise & Domains
Machine Learning & Predictive Analytics Machine Learning Engineer specialization in supervised learning, unsupervised learning, deep learning, ensemble methods, time series forecasting, demand prediction, sales forecasting, churn prediction, recommendation systems, clustering, classification, regression analysis, predictive maintenance.
AI Engineering & Natural Language Processing (NLP) AI Engineer expertise in Generative AI, Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), chatbots, conversational AI, sentiment analysis, text classification, document processing, knowledge extraction, AI agents, automation systems.
Data Science & Advanced Analytics Data Scientist proficiency in statistical analysis, hypothesis testing, A/B testing, exploratory data analysis (EDA), data visualization, business intelligence, anomaly detection, pattern recognition, feature engineering, data mining, fraud detection, personalization.
Computer Vision & Deep Learning AI Engineer experience in convolutional neural networks (CNNs), image classification, object detection, image segmentation, transfer learning, neural network optimization, model deployment.
MLOps & Data Engineering Machine Learning Engineer skills in model deployment, CI/CD pipelines, Docker containerization, cloud computing (AWS, GCP, Azure), data pipelines, ETL processes, model monitoring, scalable ML systems, LLMOps.
Tech Stack: Python, R, SQL, scikit-learn, Apache Spark, pandas, polars, AWS, TensorFlow, PyTorch, XGBoost, LightGBM, OpenAI API, Hugging Face, Transformers, AWS SageMaker, Docker, Kubernetes, Apache Airflow, Tableau, Power BI, AWS Athena, PostgreSQL.
✨ Why Clients Choose Me
- Business-first approach: Focus on ROI and measurable outcomes that increase revenue and improve efficiency
- Production-ready solutions: Machine Learning models that scale and deliver consistent results
- Fast delivery: Most projects completed within 2-4 weeks
- Full-stack capability: From Data Scientist analysis to AI Engineer deployment
- Proven track record: 50+ successful projects with quantified business impact
🚀 Ready to Get Started?
Send me a message with your data challenge, timeline, and budget range. I'll respond within 4 hours with a tailored approach and clear ROI projections.
Transform your data into competitive advantage - let's build something measurable and impactful that drives real business results.
Steps for completing your project
After purchasing the project, send requirements so Vladyslav can start the project.
Delivery time starts when Vladyslav receives requirements from you.
Vladyslav works on your project following the steps below.
Revisions may occur after the delivery date.
Project Understanding & Data Collection
We’ll discuss your goals, project scope, and gather your data (CSV, Excel, database, or API). I’ll review the data structure and clarify requirements.
Data Cleaning & Exploratory Data Analysis (EDA)
I’ll clean the dataset, handle missing values, and run detailed data analysis to uncover trends, distributions, and outliers using Python libraries (Pandas, Seaborn, etc.).