Do you often hear about artificial intelligence in the news and want to learn more about it?
Do you find a machine’s ability to learn interesting and would like to understand how an AI works deep down?
Are you already in the field of machine learning and you want a reliable font of valuable information?
Are you searching for a blog where you can learn something useful for your present and future? If so, you’re in the right place, Inside Algorithms!
Table of Contents
What is machine learning?
Machine learning is a subfield of artificial intelligence that studies the development of algorithms that can learn patterns from given input data and make predictions based on them.
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.
Why study machine learning?
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.
It is important to be informed about such an influential topic that will affect our daily lives more and more.
My experience in the field
I’ve been attracted to computers and the internet since I was a child, but I started my journey two years ago when I approached coding by making websites in HTML and CSS (markup languages that underlie the web).
After a year of web development, I started learning Python, a programming language useful in camps such as automation and data analysis.
After I understood Python basics, I dived into the machine learning field. I coded a house prices calculator, a brain cancer recognizer model, and much more.
Inside Algorithms topics
Inside Algorithms blogs covers all the processes for developing and using artificial intelligence, which is not only it’s training, but also managing and manipulating data, evaluating the accuracy of the model, and making sure it has no ethnic and cultural biases.
Who can read this blog?
Although machine learning is not an easy topic to understand, I always try to make my explanations understandable to everyone.
In complex explanations, I make sure to never just blurt out the mathematical formula, but to include the logical reasoning behind it to enhance learning for everyone, expert and non-expert.
Why follow this blog?
Clear and deep explanations
Making machine learning simple and interesting is my mission. I use pictures and videos to facilitate learning, and I also include logical reasoning behind complex mathematical formulas in my explanations.
Real-life projects and examples
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.
Create your own artificial intelligence
With step-by-step tutorials you will be able to program your artificial intelligence, choosing input data of topics you are interested in and algorithms you think are most efficient.