Sesha Venkata Sriram Erramilli's repositories
Concrete-Compressive-Strength-Prediction
The aim of this project is to develop a solution using Data science and machine learning to predict the compressive strength of a concrete with respect to the its age and the quantity of ingredients used.
Credit-card-fraud-detection-system
This fraud detection system is powered by a Machine Learning model, which accurately identifies whether an initiated transaction is fraudulent.
Credit-Card-Lead-Prediction-Model
A classification model built using Gradient Boosting classifier algorithm and deployed using flask framework, gunicorn and Heroku.
Customer-Lifetime-value-Analysis-on-Amazon-Retail-sales-data
The aim of this project is to build a cost efficient Data Warehouse on Amazon's Retail sales data and perform Customer lifetime value analyses
Pharmaceutical-customer-segmentation
Segment the customers (Physicians) which helps the pharmaceutical company to target the group having the highest nRx to tRx ratio, eventually boosting up the drug sales.
Text-Classification-using-Naive-Bayes-Algorithm
This project is about classifying the text using a Naive bayes classifier.
Complete-Python-3-Bootcamp
Course Files for Complete Python 3 Bootcamp Course on Udemy
darknet
YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
Databricks-Certified-Data-Engineer-Associate
The resources of the preparation course for Databricks Data Engineer Associate certification exam
infybatch2web
a website site through collaboration-infybatch2
keras
Deep Learning for humans
Machine-Learning-Collection
A resource for learning about ML, DL, PyTorch and TensorFlow. Feedback always appreciated :)
Object-Detection-Metrics
Most popular metrics used to evaluate object detection algorithms.
pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
review_object_detection_metrics
Object Detection Metrics. 14 object detection metrics: mean Average Precision (mAP), Average Recall (AR), Spatio-Temporal Tube Average Precision (STT-AP). This project supports different bounding box formats as in COCO, PASCAL, Imagenet, etc.
scrcpy
Display and control your Android device
t81_558_deep_learning
Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks
yolov4-deepsort
Object tracking implemented with YOLOv4, DeepSort, and TensorFlow.
YOLOX
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/