Pinned Repositories
Amazon_Clone
This project is a clone of the Amazon.com home page, created using HTML and CSS. It replicates the layout and design of the Amazon home page, including the header, navigation menu, main content area, and footer.
Bharat_Intern_Task_1
Task 1 Submission
Salesforce_Clone
Student_Performance_in_Exam_Prediction_usingML_Algorithms
This repository contains an analysis of a dataset on the performance of students in exams. The dataset explores various factors that may influence students' academic outcomes, including demographic information, parental background, test preparation, and final exam scores.
Temperature_Converter_1
Task 2 Submission
Web-Based-Application-for-Plant-Disease-Prediction-using-Deep-learning
Welcome to the GitHub repository for my Plant Disease Detection project, a comprehensive solution for identifying and diagnosing plant diseases using deep learning techniques. This project was developed using Google Colab and PyCharm, leveraging the power of machine learning libraries such as TensorFlow and Keras.
Shivamjha5925's Repositories
Shivamjha5925/Amazon_Clone
This project is a clone of the Amazon.com home page, created using HTML and CSS. It replicates the layout and design of the Amazon home page, including the header, navigation menu, main content area, and footer.
Shivamjha5925/Bharat_Intern_Task_1
Task 1 Submission
Shivamjha5925/Salesforce_Clone
Shivamjha5925/Student_Performance_in_Exam_Prediction_usingML_Algorithms
This repository contains an analysis of a dataset on the performance of students in exams. The dataset explores various factors that may influence students' academic outcomes, including demographic information, parental background, test preparation, and final exam scores.
Shivamjha5925/Temperature_Converter_1
Task 2 Submission
Shivamjha5925/Web-Based-Application-for-Plant-Disease-Prediction-using-Deep-learning
Welcome to the GitHub repository for my Plant Disease Detection project, a comprehensive solution for identifying and diagnosing plant diseases using deep learning techniques. This project was developed using Google Colab and PyCharm, leveraging the power of machine learning libraries such as TensorFlow and Keras.