Machine learning is a subset of artificial intelligence that enables systems to learn and improve from experience without explicit programming. It includes various types such as artificial neural networks, pattern recognition, and reinforcement learning, with applications ranging from medical diagnosis to self-driving cars. The collection of data plays a crucial role in training these systems, while privacy concerns arise from the extensive data usage.

1. Machine learning

2. What Is Machine
learning
Machine learning is an
application of Artificial
intelligence (AI) that provides
systems the ability to automatically
learn and improve from experience
without being explicitly
programmed.

3. History
Arthur Samuel, an American pioneer
in the field of computer gaming and
artificial intelligence, coined the term
"Machine Learning" in 1959 while at
IBM

4. Schematic representation of Working
Of ML
Raw Dataset
Data
Cleaning
Feature
Selection
Training the
model
Classifier
Testing With
The
Testset

5. Techniques and types of Machine learning
1. Artificial neural network
2. Pattern recognition
3. Reinforcement learning
4. Statistical inference
5. Supervised learning
6. Clustering
7. Ensemble algorithms
Many more…….

6. Artificial neural network
Artificial neural networks (ANNs) or
connectionist systems are computing
systems vaguely inspired by the
biological neural networks that
constitute animal brains
The original goal of the ANN approach
was to solve problems in the same way
that a human brain would

7. Pattern recognition
Pattern recognition is a branch of
machine learning that focuses on the
recognition of patterns and regularities
in data, although it is in some cases
considered to be nearly synonymous
with machine learning

8. Application Of Machine Learning
1. Image searching in search engines.
2. Used for Medical Purpose.
3. Used in voice recognition systems.
4. Used for translations.
5. Used in video gaming.
6. Used in self Driving cars.
7. For Visually impaired people.
8. To get recommendations.
9. Can also be used in industries for separating and packing the products.
10.Used in Autopilot systems.
And so on…..….

9. Application in Medical
To diagnose diabetes
First the data is collected in the form
of images . Here the images of the back
of the retina are taken ang are compare
with the image of an diabetic eye.
Normal Eye

10. Translation
Translate is based on something called
"statistical machine translation". This
means that they gather as much text as
they can find that seems to be parallel
between two languages, and then they
crunch their data to find the likelihood
that something in Language A
corresponds to something in Language
B.

11. Self Driven Cars
The car are
trained by
supervised
machine
learning

12. How the data is collected
The data is collected
from everywhere . That
is what we search,
which music we listen
to, which video we
watch,were we travel.
overall what is our
interest

13. But what about Privacy

14. “I visualize a time when
we will be to robots what
dogs are to humans, and
I’m rooting for the
machines.” —Claude

15. Thankyou