Holberton School Machine Learning Projects

🤖 Intro

This repository contains the Machine Learning projects that we've done at Holberton School which includes:

• The important Mathematics Algorithms needed for the ML process:
  • Linear Algebra
  • Calculus
  • Probability
• Machine Learning Algorithms:
  • Classification
  • Regularization
  • Optimization
  • Error Analysis
  • Convolutional Neural Networks
  • Deep Convolutional
  • Architectures
  • Transfer Learning
  • Object Detection
  • Face Verification
  • Neural Style Transfer
  • Recurrent Neural Networks
  • Deep Recurrent Architectures
  • Natural Language Processing
  • Time Series Analysis
  • Dimensionality Reduction
  • Clustering
  • Hidden Markov Models
  • Neural Style Transfer

🤖 What is Machine Learning

Let's define it first in a simple way as Arthur Samuel described in 1959:

👉 Field of study that gives computers the ability to learn without being explicitly programmed

The modern definition is by Tom M. Mitchell:

👉 A computer program is said to learn from experience E with respet to some class of tasks T and performane measure P, if its performance at tasks in T, as measured by P, improves with experience E

🧑🏻‍💻 Example: playing checkers
E is the experience of playing many games of checkers
T is the task of playing checkers
P is the probability that the program will win the next game

🤖 Technologies needed

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By Khouloud Software engineer at HolbertonSchool®️