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Best Russian-speaking scikit-learn freelancers to hire in 2025

Looking to hire Russian-speaking scikit-learn freelancers for your next project? Browse the world’s best scikit-learn freelancers on Contra.

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Alexey Golovnia
Poland
Cover image for Return Prediction
Cover image for Archive Transformation
Cover image for Directory Export Tool
Cover image for Document Video Registration
scikit-learn(1)
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Aliaksei Chymba
Belarus
Cover image for Question Answer App for Medicine Instructions
Cover image for Stable Diffusion Fine-Tuning
Cover image for Sentiment Analysis of Financial Records
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Michael Tawk
Lebanon
Cover image for Predict Remaining Life of Pipe
Cover image for Predicting Lira Price Through Twitter Data Analysis
Cover image for Data Visualization Using Power BI
Cover image for Sales Forecasting System
scikit-learn(1)
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Odilbek Tokhirov
Uzbekistan
Cover image for Loan Grade Prediction
Cover image for Employee Salaries Analysis
Cover image for RAG Chatbot
Cover image for Land Cover Classification
scikit-learn(1)
Cover image for Humana Mays Healthcare Analytics Case Competition (2021)
Cover image for 
Satellite position and velocity prediction system (IDAO 2020)
Cover image for AI-Powered Student Engagement Platform, Co-Founder (2024)
Cover image for Social AI, Co-Founder (2024)
scikit-learn(2)

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FAQs

Look for skills in Python programming and understanding of machine learning concepts. The freelancer should be comfortable with data processing, model building, and model evaluation using scikit-learn. Knowledge of data visualization tools can also be helpful for presenting results.
Ask for examples or a portfolio of their previous projects. Look for how they used scikit-learn in different machine learning tasks like classification or clustering. Notice if they provide clear explanations and data visualizations in their project summaries.
Expect clear and well-documented code in Python. The freelancer should provide predictive models along with reports on their performance metrics. Data visualizations illustrating the model's predictions and patterns in the data can also be expected.
Communicate clearly about your goals and the problems you want to solve. Use simple terms and avoid technical jargon. Make sure the freelancer asks clarifying questions to better understand your requirements.
Ask about their approach to handling missing data or large datasets. Request explanations of how they choose algorithms for different tasks like regression or clustering. Inquire if they have experience with similar projects to yours.
Discuss the project's scope and deadlines right from the start. Set milestones for different phases such as data preparation, model development, and final delivery. Regular check-ins to review progress can help ensure timelines are met.
Clearly define what success looks like for your project. Discuss the specific outputs you want, such as reports or model accuracy. Ensure there's agreement on how these goals will be measured and evaluated throughout the project.
Use project management tools to keep track of tasks and deadlines. Request regular updates or brief reports from the freelancer. Visual demonstrations or presentations can also help to see the progress and validate project milestones.
Set up criteria for quality measures like accuracy, precision, or F1-score for the models. Require that the freelancer provides results from cross-validation or testing. Ensure they document their work process so another expert could understand and replicate it.
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