This document provides an overview of machine learning and neural networks. It explains that machine learning uses algorithms to learn from data without being explicitly programmed, and can now be programmed to learn autonomously and work more efficiently. Neural networks similarly mimic the human brain by using mathematical formulas to constantly adapt to new information without following fixed instructions. The document compares how neural networks function to the human brain's ability to process information through the senses and shift processing between billions of neurons based on experiences.

1. BASICS ABOUT ARTIFICIAL
INTELLIGENCE – PART 1

2. MACHINE LEARNING
BASICS
ANTONIO FERNANDES, M.D.
NEURORADIOLOGIST, DEEP LEARNING
ENTHUSIASTIC IN BRAIN AND SPINE IMAGING

3. Machine Learning
 ML is a method of data analysis that incorporates the utilization of algorithms
that have the capabilities to learn from data without programming
 Computer science svvvv AI (a branch CS) ML (application of AI)

4. Machine Learning: GET SIMPLE!
 The world is full of data. Then use algorithms to predict and work for you. YOU
CAN NOT AVOID ML
 Machines and computers now do not need to have every detail programmed.
They can be programmed to learn by themselves and to work more efficiently.
 Human mind is multitasking and flexible. Computes are not yet there but each
year they are capable of doing more and more complex things

5. Neural Networks
 Neural Networks can look like science fiction but they are too real.
 NN are a series of mathematical formulas (algorithms) mimicking human brains
 NN can constantly adapt to new information and changes
 Using NN computers constantly adapt and don’t follow always the same
instruction (mimicking brains- At least some brains!!!)

6. Neural Networks -Brain
HUMAN GAIN
EXPERIENCE BY
THE 5 SENSES
THE BRAIN PROCESSES THE
INFORMATION AND
COMPARE WITH PREVIOUS
EXPERIENCES
CONLCUSION
SIMILAR TO
ML AND NN
PASSWAYS
OF THINKING
are constantly
shifting
between
billions of
neurons

7. VERY IMPORTANT NOTE
 Machine Learning for Beginners. Guide to understanding Machine Learning.
Matthew Kinsey. 2018.
 This presentation is a brief summary using sentences of the book above and
is used without any permission of the trademarks, brands or authors. This is
for clarifying purposes only and I am not the author of them.