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Hey! šŸ‘‹

Iā€™m Saurabh Bhardwaj, a Freelancer Machine Learning Engineer and Data Scientist.

Skills

  • Programming:

  • Machine Learning: Data Engineering, Data Analysis, Predictive Modelling, NLP, Computer Vision
  • Software Development: Git, GitHub, Version Control, DVC, CI/CD, Dockers, Kubernates, Terraform, MLOPs
  • Others: SQL, NO-SQL, Tableau, Weight & Bias and MLFlow pipeline, AWS SageMaker, Azure DevOps

Education

  • MSc-Applied Artificial Intelligence Cranfield University, UK.

  • B-Tech: Mechanical Engineering Gautam Buddha Technical University, India.

Contact

šŸ“§ [email protected] šŸ“« LinkedIn šŸ“« Twitter

Saurabh Bhardwaj's Projects

agile-development-with-azure icon agile-development-with-azure

A project to demonstrate and perform continuous delivery for a Python-based machine learning application using the Flask web framework.

analyze_a-b_test_results icon analyze_a-b_test_results

A project to understand the results of an A/B test run by an e-commerce website. The company has developed a new web page in order to try and increase the number of users who "convert," meaning the number of users who decide to pay for the company's product.

finance-complains-classification icon finance-complains-classification

An end-to-end machine learning real time project to classify the type of finance complains to understand the impact on an organisation.

generative-ai-for-beginners icon generative-ai-for-beginners

18 Lessons, Get Started Building with Generative AI šŸ”— https://microsoft.github.io/generative-ai-for-beginners/

hangman icon hangman

An Python implementation of the Hangman game, where the computer thinks of a word and the user tries to guess it.

heart_failure_prediction icon heart_failure_prediction

An end-to-end Machine Learning Project with in-depth data analysis, data visualisation, feature engineering, feature selection and model selection using complex ML techniques such as SVM, Random Forest, Logistic Regression, XG Boost, Naive Bayes, and Decision Tree algorithms with 85% final model accuracy.

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