Srishti Chauhan's starred repositories
MLAlgorithms
Minimal and clean examples of machine learning algorithms implementations
Data-Structures-and-Algorithms
Crisp and self explanatory codes for various DSA Problems from online platforms like Geeksforgeeks and leetcode
DSA_notes_and_resources
This Repo contains resources which I used while learning DSA, questions and their solutions by me.
A-HIOT
A-HIOT stands for automated hit identification and optimization tool which comprise of the stacked ensemble, deep learning architectures and combines conventional approaches based on the chemical space (AI-dependent predictive model derived from standard ligand information for respective targets) and protein space (target structure information collection and artificial intelligence dependent model extracted from the interaction pattern of target protein-ligand complexes).
Data_Structure
Algorithms implemented in python
HeartHealthPredictor
The major reason for the death in worldwide is the heart disease in high and low developed countries. The data scientist uses distinctive machine learning techniques for modeling health diseases by using authentic dataset efficiently and accurately. The medical analysts are needy for the models or systems to predict the disease in patients before the strike. High cholesterol, unhealthy diet, harmful use of alcohol, high sugar levels, high blood pressure, and smoking are the main symptoms of chances of the heart attack in humans. Data Science is an advanced and enhanced method for the analysis and encapsulation of useful information. The attributes and variable in the dataset discover an unknown and future state of the model using prediction in machine learning. Chest pain, blood pressure, cholesterol, blood sugar, family history of heart disease, obesity, and physical inactivity are the chances that influence the possibility of heart diseases. This project emphasizes to evaluate different algorithms for the diagnosis of heart disease with better accuracies by using the patient’s data set because predictions and descriptions are fundamental objectives of machine learning. Each procedure has unique perspective for the modeling objectives. Algorithms have been implemented for the prediction of heart disease with our Heart patient data set