Python Project-1||Build a Vending Machine|| Part-4|| Functions

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Python Project-1||Build a Vending Machine|| Part-4|| Functions

As you are aware, we are living in a world where data is the electricity because it is one of the important features of every organization. It helps business leaders to make decisions based on facts, statistical numbers, and trends. There is a massive data explosion that has resulted in the culmination of new technologies and smarter products such as Artificial intelligence/Machine learning, IoT, Big data etc. and we are just landing to an era where these technologies rule the world.
The important question here is are we equipped enough for this technology transformation? We are helping you to transform the world we live in using advanced technologies. The objective of this course is to give an introduction to machine learning concepts- which needs a strong foundation of mathematics and programming skills

In this session, we start using all python techniques to build a vending machine!! yes, we apply all the knowledge gained from previous lectures to get started with a wonderful project.
Vending Machine Applications:
Hand sanitizer/Mask/ Soap dispensing Vending Machine
Napkin Dispenser
Snacks & Food Vending Machine
Tea/Cofee Vending Machine
Ration Vending Machine
Dairy products Vending Machine
Pharmacy Vending Machine
Vending Machine Locations:
Apartment Communities
Hotels
Manufacturing Facilities.
Offices.
Retail Stores.
Public places

This covers the below Topics:
1. Introduction to Machine learning- Need for AI/ML, why to learn AI/ML, machine learning types, supervised,unsupervised and reinforced learning, application, difference between Human thinking Vs Machine thinking, difference between programming vs Machine learning.
2. Mathematics for Machine learning- Trigonometry, linear algebra, matrices, calculus & probability.
3.Python for Machine learning- variables, different libraries needed for data science such as numpy, pandas, matplotlib, etc
4. Deep-dive into machine learning- How ML algorithm works, the concept of cost function and gradient descent, practical examples for linear regression and Classifications, ML Algorithms and its usage.
5.Introduction to OpenCV- Image/video processing with OpenCV
6. Face recognition- Building a security alarm system using ML techniques

[PaulESP-ge]

thank you sir, Really helpful to understand