My project objectives is to Analyze features Of the Speed Limit Sign. Use the video data coming in to identify the speed written on the sign post and then using OpenCV technology with the Raspberry Pi to detect the Speed limit sign to make the car drive according to the speed read by the camera

Uses deep learning techniques such as single shot multi-box object detection and transfer learning to teach PiCar to detect speed limit signs on the road. Using Tensor flow we will teach it to change its speed limit according to the posted speed signs.

The objective of the system is to make reservation process easier and stable to customers. The application would have features that would make effective flight management and these include a web based internet booking system , proper validation to use correct data and eliminate the costly searching process . Also using more optimized code with latest technologies including Inventory control and payment system to make working process easier. The project provides the customer with every details of the airlines.

The customer/ passenger can make a reservation by making a , view flights, add and delete a flight, add booking, be able to view the booking , modify the booking, delete a booking. The admin plays an important role in the management of this system. In this project, the user has to perform all the main functions from the admin side.the user can register or the admin can add a passenger. For that, the admin can take the personal details of the customer. Not only this, the system allows the user to even cancel the reservation and then reserve another flight ticket. Key features of this management included;

1. 1.Login System
2. 2.Register passenger
3. 3.Manage passenger

Spring Tool Suite has been used in developing all spring boot API’s. All the business and backend API logic has been implemented in Java Spring boot. MySql database has been used. For the project and overall project will be. Running on Tomcat Server. All frontend logic has been implemented over the Angular and. Used angular 14. and for Angular IDE we used. Visual Studio Code.All the Validations tasks and animations are developed by JavaScript whereas. Page layout has been designed in HTML and also CSS has been used for all the designing part

My project as an aspect of Data Science analyses private data of Bank Customers with goals to discover key insights from the bank customers database and study the customers’ demographics such as customer (gender, age, and location). Also, I incline to understand the company’s product and customer’s financial history such as customer (credit score, estimated salary, balance, tenure, credit card possession, etc.). Lastly, how variable such as customers demographics and financial history affects the customers churn rate. The web application ia aimed at performing analysis and developing a prediction model for the bank customer churn.

In this project I will use CRISP-DM to build the bank customer churn prediction model in this methodology , a 5 phase technique was used ;

1. 1.Data Collection
2. 2.Data Understanding
3. 3.Data Preprocessingr
4. 4.Modelling and Evaluation
5. 5.Model Deployment