BrahmG
Machine Learning Enthusiast . Software Engineer at Soroco. . LinkedIn: https://cutt.ly/qkkZ4i
SorocoNew Delhi
Pinned Repositories
Getting_started_with_TFLite
How to generate super resolution images using TensorFlow Lite
Music-Player-Pygame
Zomato_case_study
-TheSparkFoundation
TheSparkFoundation tasks
anagrams
anagrams_starter
AnalyticsVidhya_Competitions
AnalyticsVidhya_HR-Analytics_Hackathon
applied
applied-CS-Brahm
repository to showcase the projects made
BrahmG's Repositories
BrahmG/djangorest
sample app using vagrant
BrahmG/django_base
sample app
BrahmG/blogprojectdrf
You can use this repo to deploy application on AWS using CodePipeline
BrahmG/Lushlyrics-insecure
BrahmG/orders-api
basic microservice using GO and CHi
BrahmG/react-practice
BrahmG/Django_1
BrahmG/Dynamic-Programming
BrahmG/Coding-Questions-with-Answers
commonly asked questions in interviews with solutions.
BrahmG/Dice_roll_game
BrahmG/Building-a-Simple-Web-Browser-in-Python
BrahmG/Eda_on-_Reddit_Data
BrahmG/Denoising_Autoencoder.ipynb
Auto Encoders for De-noising the data.
BrahmG/Zomato_case_study
BrahmG/Image_Caption_on_flickr8k_dataset
BrahmG/Google_Analytics_Revenue_Prediction-Case-Study
BrahmG/Music-Player-Pygame
BrahmG/LSTM_ON_DONORS_CHOOSE_DATASET
BrahmG/FACEBOOK_FRIENDS_RECOMMENDATION
BrahmG/MicrosoftMalwareDetection
BrahmG/DECISION_TREE_ON_DONORS_CHOOSE_DATASET
BrahmG/NAIVE_BAYES_ON_DONORS_CHOOSE_DATASET.
BrahmG/Implementing-Custom-RandomSearchCV
BrahmG/Exploratory_Data_Analysis-On-Haberman-Dataset
BrahmG/YOLO-Object-Detection
YOLO-Object-Detection YOLO is a state-of-the-art, real-time object detection algorithm. In this notebook, we will apply the YOLO algorithm to detect objects in images. darknet prints out the objects it detected, its confidence, and how long it took to find them. We didn't compile Darknet with OpenCV so it can't display the detections directly. Instead, it saves them in predictions.png. You can open it to see the detected objects. Since we are using Darknet on the CPU it takes around 6-12 seconds per image. If we use the GPU version it would be much faster. How to run: Open Jupter Notebook in your browser Open the folder containing this folder Run YOLO.ipynb
BrahmG/Tom-and-Jerry-Emotion-Detection-Challenge
BrahmG/HackerEarth_Deep_Learning_Challenge_Snakes_in_the_hood
HackerEarth_Deep_Learning_Challenge_Snakes_in_the_hood
BrahmG/Getting_started_with_TFLite
How to generate super resolution images using TensorFlow Lite
BrahmG/quantum
Hybrid Quantum-Classical Machine Learning in TensorFlow
BrahmG/HackerEarth-Machine-Learning-Challenge-Love-in-the-time-of-screens
https://www.hackerearth.com/challenges/competitive/hackerearth-machine-learning-challenge-predict-match-percentage/