1. Advances in Machine Learning
Presented by
Yogasathish S
THE OXFORD COLLEGE OF ENGINEERING
BOMMANAHALLI, HOSUR ROAD, BANGALORE68
DEPARTMENT OF MCA
2. Advances in Machine Learning
Definition
Machine learning is a field of artificial intelligence that allows systems to learn
and improve from experience without being explicitly programmed. It is
predicated on the notion that computers can learn from data, spot patterns, and
make judgments with little assistance from humans.
Good quality data is fed to the machines, and different algorithms are used to
build ML models to train the machines on this data. The choice of algorithm
depends on the type of data at hand and the type of activity that needs to be
automated.
7. It is mandatory to learn a programming language, preferably Python, along with the
required analytical and mathematical knowledge. Here are the five mathematical
areas that you need to brush up before jumping into solving Machine Learning
problems:
• Linear algebra for data analysis: Scalars, Vectors, Matrices, and Tensors
• Mathematical Analysis: Derivatives and Gradients
• Probability theory and statistics for Machine Learning
• Multivariate Calculus
• Algorithms and Complex Optimizations
8. Advances in Machine Learning
The goal of true artificial intelligence (a computer or program that thinks and
communicates like a human being) has not yet been achieved. However, individual
machine learning programs have been trained to specialize in performing certain tasks
that are quite useful.
For a variety of reasons, machine learning is often referred to as AI. Combinations of a
wide variety of machine learning programs, acting as subprograms, have the potential
to support the goal of true artificial intelligence.
9. Advances in Machine Learning
Virtual Assistants
These machine learning assistants are some of the most advanced forms of artificial intelligence
currently on the market.
While they can’t discuss philosophy, they can understand basic commands and have a fairly
large vocabulary.
Virtual assistants can help with daily tasks, such as making calls, providing reminders of meetings,
managing to-do lists, and taking notes.
Some of the more advanced ones (Flamingo AI) can reduce research time by up to 75 percent.
They augment human research by finding information within the organization’s silos.
10. Advances in Machine Learning
Alexa is a virtual assistant that is created by Amazon and is also known as Amazon Alexa. This virtual
assistant was created using machine learning and artificial intelligence technologies.
Similar to Alexa, Siri is also a virtual or a personal assistant. Siri was created by Apple and makes use of
voice technology to perform certain actions. Siri also makes use of machine learning and deep learning to
function.
Machine Learning is used in our daily lives much more than we know it. These are areas where it is used:
• Facial Recognition
• Self-driving cars
• Virtual assistants
• Traffic Predictions
• Speech Recognition
• Online Fraud Detection
• Email Spam Filtering
• Product Recommendations
11. Advances in Machine Learning
Chat bots
ML Algorithms for Writing ML Algorithms
NLP
Graph Neural Networks
13. How does GENERATIVE AI works?
Generative AI starts with a prompt that could be in the form of a text, an image, a
video, a design, musical notes, or any input that the AI system can process. Various
AI algorithms then return new content in response to the prompt. Content can
include essays, solutions to problems, or realistic fakes created from pictures or
audio of a person.
Early versions of generative AI required submitting data via an API or an otherwise
complicated process. Developers had to familiarize themselves with special tools
and write applications using languages such as Python.
Now, pioneers in generative AI are developing better user experiences that let you
describe a request in plain language. After an initial response, you can also
customize the results with feedback about the style, tone and other elements you
want the generated content to reflect. .
16. How could generative AI replace jobs
Writing product descriptions.
Creating marketing copy.
Generating basic web content.
Initiating interactive sales outreach.
Answering customer questions.
Making graphics for webpages.
