LATEST POSTS
What is a probability of an event? Classic formula and examples
Definition of probability Probability is a word that we use a lot in our everyday life. Winning the lottery and being struck by lightning is very unprobable. Instead, receiving a…
Introduction to probability theory
What is probability theory? Most phenomena in our lives are partially random. Think about weather forecasting, the stock market, and football game outcomes. These are all things we can’t exactly…
What is bagging in ensemble learning?
What is bagging? Bagging is a parallel ensemble learning technique that trains multiple weak models on different datasets and averages their predictions. The bagging algorithm Problem statement We have a…
Ensemble learning, boosting and bagging
What is ensemble learning? Ensemble learning is a machine-learning approach where we train numerous simple models and aggregate their predictions. These simple models are called weak learners. What is an…
The derivative of a function explained clearly
Suppose we have a graph representing the population of a village as a function of time.Let us take two time instants on the x-axis where the population is equal. Now…
WHAT IS MACHINE LEARNING ?
Machine learning (ML) is a subfield of artificial intelligence that studies the development of algorithms that can learn patterns from data and make predictions based on them. These "human-like intelligent" systems are called models.
Machine learning it's a broad field that also includes processing input data, evaluating model accuracy and managing AI influence on society, ensuring these products aren't affected by gender, ethnic, and cultural biases.
In today's world, machine learning solutions are becoming increasingly important. They are applied in various sectors like natural language processing, computer vision, speech recognition, email filtering, agriculture, and medicine.
ABOUT THIS BLOG
Inside Algorithms is a constantly updated blog with articles regarding machine learning, which studies the development of artificial intelligence algorithms.
Thanks to Inside Algorithms you will learn how artificial intelligence like ChatGPT works in the core and how to apply your knowledge to real-world scenarios. Cool isn’t it?
ABOUT THIS BLOG
Inside Algorithms is a constantly updated blog with articles regarding machine learning, which studies the development of artificial intelligence algorithms.
Thanks to Inside Algorithms you will learn how artificial intelligence like ChatGPT works in the core and how to apply your knowledge to real-world scenarios. Cool isn’t it?
POST TOPICS
Fundamentals
Fundamentals concepts of machine learning
Feature engineering
Data management methods to provide more meaningful input data
ML Algorithms
Algorithms that can learn relationships between data to make predicitons
Validation
Different techniques for measuring the accuracy of a model
Real-life projects
Program artificial intelligence models with real-life data and goals
WHY FOLLOW THIS BLOG?
Clear explanations
I struggle with math, so in order to understand the concepts I have to make an effort to find simple and clear explanations. These solutions are the ones I share with you.
Algorithms from scratch
Another thing that helps me fully understand machine learning algorithms is to rewrite them from 0. I forget about all the convenient modern Python libraries and just use math.
Real-life projects
Through examples and projects taken from real situations, with real datasets and true queries, you will be able to better learn this discipline and develop a practical view of theoretical concepts.
Machine intelligence is the last invention that humanity will ever need to make.
– Nick Bostrom, philosofer and AI expert