Neemias Buceli Portfolio

Context

Hello guys, welcome to my Data Science Portfolio. I include some knowledges I earn in my journey. I'll include some case study, papers, and code.

Note: This repository was created recently and I upgrade as soon as I can.

Table of Contents

• Pogramming Skills;
• Math & Stat;
• Machine Learning.

Math & Stat

• Fundamental of Statistic;
  • Population vs Sample;
  • Mean;
  • Variance;
  • Standard Deviation (STD);
  • Correlation;
  • Covariance;
  • Probability Distribution Functions;
  • Bayes Theorem.
• Bootstraping;
• Expectation Algorithm;

Programming Skills

• Code Challenge;
• knapsack-problem-using-dp-grasp-tabu;
  • Dynamic programming;
  • Grasp Heuristic;
  • TABU Search.

Machine Leaning

• Machine Leaning Algorithms - Tutorial;
  • Regression in Convolutional Neural Network for Applied to Plant Leaf Count;
  • Case Studies: Data Science Projects;
  • Forecasting Data Analysis;
• Pattern Recognition:
  • Linear Algebra - Singular Value Decomposition;
    • Vector Calculus;
    • Probability and Distribution;
    • Optimization and Convex Optimization.
    • Machine Learning Algorithm:
      • Linear:
        • Perceptron;
        • Adaline;
        • Logistic Regression.
      • Non Linear:
        • SVM;
        • Decision Tree;
        • Random Forest;
        • Adaboost;
        • Gradient Boosting;
        • XGBoost.