{"id":23918118,"url":"https://github.com/neemiasbsilva/datascience-portfolio","last_synced_at":"2026-05-14T18:33:32.370Z","repository":{"id":54823090,"uuid":"521985731","full_name":"neemiasbsilva/datascience-portfolio","owner":"neemiasbsilva","description":"Hello guys, welcome to my Data Science Portfolio. I include some knowledges I earn in my journey. I included some case study, papers, and code. 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Here, I showcase the insights and skills I have acquired throughout my journey in the field. You’ll find a collection of case studies, research papers, and code that illustrate my work and expertise.\n\nNote: I regularly update this repository with new projects and links to additional repositories for more complex projects that exceed the scope of this one. Stay tuned for more exciting updates!\n\n## Table of Contents\n\n- [Math \u0026 Stat](#math--stat);\n- [Pogramming Skills](#programming-skills);\n- [Machine Learning](#machine-leaning);\n- [Deep Learning](#deep-learning).\n\n## Math \u0026 Stat\n\n- [Fundamental of Statistic](https://github.com/neemiasbsilva/NeemiasBuceli-ds-portfolio/tree/main/mathematic-and-statistics/fundamental-of-statistics);\n  - Population vs Sample;\n  - Mean;\n  - Variance;\n  - Standard Deviation (STD);\n  - Correlation;\n  - Covariance;\n  - Probability Distribution Functions;\n  - Bayes Theorem.\n- [Bootstraping](mathematic-and-statistics/bootstrapping);\n- [Expectation Algorithm](mathematic-and-statistics/expectation_algorithm);\n\n## Programming Skills\n\n- [Code Challenge](https://github.com/neemiasbsilva/programming-skills);\n- [knapsack-problem-using-dp-grasp-tabu](https://github.com/neemiasbsilva/knapsack-problem-using-dp-grasp-tabu);\n  - Dynamic programming;\n  - Grasp Heuristic;\n  - TABU Search.\n\n## Machine Leaning\n\n- [Machine Leaning Algorithms - Tutorial](https://github.com/neemiasbsilva/machine-learning-algorithm);\n- [Case Studies: Data Science Projects](https://github.com/neemiasbsilva/case-study-data-science);\n- [Forecasting Data Analysis](forecasting/);\n- [Pattern Recognition](pattern-recognition/):\n  - Linear Algebra - Singular Value Decomposition;\n    - Vector Calculus;\n    - Probability and Distribution;\n    - Optimization and Convex Optimization.\n    - Machine Learning Algorithm:\n      - Linear:\n        - Perceptron;\n        - Adaline;\n        - Logistic Regression.\n      - Non Linear:\n        - SVM;\n        - Decision Tree;\n        - Random Forest;\n        - Adaboost;\n        - Gradient Boosting;\n        - XGBoost.\n- [Predict wich new visitors will come back and purchase using the Google Merchandise Store dataset](ecommerce-using-bigquery-ML).\n\n## Deep Learning\n\n- [Regression in Convolutional Neural Network for Applied to Plant Leaf Count](https://github.com/neemiasbsilva/regression-in-CNNs-applied-to-plant-leaf-count);\n- [Music Gener classification using MLFlow for tracking metrics in azure cloud](https://github.com/neemiasbsilva/music-genre-classification-mlflow-azure)\n- [MiniGPT4 for image caption generation](https://github.com/neemiasbsilva/MiniGPT4-image-caption-generation);\n- [Developing a nano GPT-2 from scratch using PyTorch and training using the Fineweb datase](https://github.com/neemiasbsilva/developing-nanoGPT2-fineweb).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fneemiasbsilva%2Fdatascience-portfolio","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fneemiasbsilva%2Fdatascience-portfolio","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fneemiasbsilva%2Fdatascience-portfolio/lists"}