-Machine learning project on analysis of data and finding the predictions.
-The user needs to give inputs like Blood pressure, Sugar, Blood Cells, Haemoglobin, etc. to predict the result.
-Connected the back end and front end with HTML (Accuracy: 91%)
-Skills: Random Forest, Neural Networks, HTML, CSS, Flask, Python

-In this project using ML and python libraries we can predict the percentage of a heart attack here we used the KNN algorithm and many graphs to show conclusions.
-I trained my model using different algorithms like KNN, SVM, PCA, and got an accuracy of approximately 85%.

-Image analysis is used to analyze around 10 types of skin diseases. OpenCV, TensorFlow was used
-Flask is connected as a user interface; the user uploads the image and the model shows the output/ disease name (Accuracy: 91.2%)
-Skills: Convolution Neural Networks, HTML, CSS, Flask, Python

-Used to calculate the estimated profit by different previous analysis
-Users can select the city, gross capital, and some requirements
-Currently, the model is trained for 3 cities( New York, Florida, California)
-Skills: Artificial Neural Networks, HTML, CSS, Flask, Python

Machine learning project on analysis of data and finding the predictions. The user needs to give inputs like Blood pressure, Sugar, Blood Cells, Haemoglobin, etc. to predict the result. Connected the back end and front end with HTML (Accuracy: 91%)

Image analysis is used to analyze around 10 types of skin diseases. OpenCV, TensorFlow was used Flask is connected as a user interface; the user uploads the image and the model shows the output/ disease name (Accuracy: 91.2%)

Analyzed the Heart rates based on different algorithms like SVM, KNN, KNN with PCA Different graphs were plotted on the different biases. Accuracy: 90%