snigdhakakkar
I am an Engineer who is quite enthusiastic about data behind the product decisions and I love to delve deeper into machine learning and deep learning problems
University of WaterlooToronto
Pinned Repositories
AudioClassificationSystem
An Audio Classification Project Using ML & DL on Urbansound8K Dataset (Kaggle): Sound Classification using Librosa, MFCC, CNN, Keras, XGBOOST, Random Forest.
COVID-19-Confirmed-Death-and-Recovered-Case-Predictions-for-US
COVID-19-Confirmed, Death and Recovered Case Predictions for US (As a part of Assignments in Data And Knowledge Management Course at University of Waterloo)
DataStructures_And_Algorithms
Housing_Price_Predictor
Kaggle dataset 'California Housing' Analysis - Machine Learning Predictor using Scikit-learn
Machine-Language-Translation-using-Sequence-To-Sequence-Neural-Networks-
Implementing English to French Language translation using Machine Learning
Online-Class-Attendance-App-Using-Face-Recognition
Attendance App Based on Face Recognition Tools used - Flask Web Framework Haarcascades xml files for facial features CSS OpenCV, Numpy, FaceRecognition, Render_template, Response, Url_for Modules from Python Python language for coding
Real-Time-Face-Mask-Detection-System
Face Mask Detection System built with OpenCV, Keras/TensorFlow using Deep Learning and Computer Vision concepts in order to detect face masks in static images as well as in real-time video streams.
Tableau_Visualizations
Effective visualizations and calculated fields for Tableau Reports for businesses
tensor-flow-zeroToMastery
Twitter_Sentiment_Analysis_Engine
Twitter is one of the widely used social media platforms. Many a times, we see strong discussion on Twitter about someone’s opinion that sometimes results in a collection of negative tweets. For gauging whether the kind of tweets are positive, negative or have a neutral sentiment, we can use this simple Twitter Sentiment Analysis Engine. Sentiment analysis is a task of natural language processing. Various social media platforms monitor the sentiments of those engaged in a discussion using such sentiment analysis engines. For the purpose of this project, I have used a Kaggle dataset about a long discussion within a group of users on Twitter. Our task was to identify how many tweets are negative and positive so that we can give a conclusion.
snigdhakakkar's Repositories
snigdhakakkar/AudioClassificationSystem
An Audio Classification Project Using ML & DL on Urbansound8K Dataset (Kaggle): Sound Classification using Librosa, MFCC, CNN, Keras, XGBOOST, Random Forest.
snigdhakakkar/DataStructures_And_Algorithms
snigdhakakkar/Online-Class-Attendance-App-Using-Face-Recognition
Attendance App Based on Face Recognition Tools used - Flask Web Framework Haarcascades xml files for facial features CSS OpenCV, Numpy, FaceRecognition, Render_template, Response, Url_for Modules from Python Python language for coding
snigdhakakkar/Real-Time-Face-Mask-Detection-System
Face Mask Detection System built with OpenCV, Keras/TensorFlow using Deep Learning and Computer Vision concepts in order to detect face masks in static images as well as in real-time video streams.
snigdhakakkar/tensor-flow-zeroToMastery
snigdhakakkar/COVID-19-Confirmed-Death-and-Recovered-Case-Predictions-for-US
COVID-19-Confirmed, Death and Recovered Case Predictions for US (As a part of Assignments in Data And Knowledge Management Course at University of Waterloo)
snigdhakakkar/Machine-Language-Translation-using-Sequence-To-Sequence-Neural-Networks-
Implementing English to French Language translation using Machine Learning
snigdhakakkar/Twitter_Sentiment_Analysis_Engine
Twitter is one of the widely used social media platforms. Many a times, we see strong discussion on Twitter about someone’s opinion that sometimes results in a collection of negative tweets. For gauging whether the kind of tweets are positive, negative or have a neutral sentiment, we can use this simple Twitter Sentiment Analysis Engine. Sentiment analysis is a task of natural language processing. Various social media platforms monitor the sentiments of those engaged in a discussion using such sentiment analysis engines. For the purpose of this project, I have used a Kaggle dataset about a long discussion within a group of users on Twitter. Our task was to identify how many tweets are negative and positive so that we can give a conclusion.
snigdhakakkar/Algorithms
Algorithms for practice
snigdhakakkar/Automobile-Mileage-Prediction-
Automobile Mileage Prediction using Multiple Regression Models in Machine Learning (Scikit-learn Python Library)
snigdhakakkar/ChatApplication
A simple chat application using Java and various Java API libraries.
snigdhakakkar/Core_Python
Exercises for learning basic python
snigdhakakkar/Corona-Virus-Covid-19-Live-tracking-India
Developed an application for tracking Covid cases using python. Also performed Exploratory data analysis to understand more about the data coming in and deduced patterns. Used Papermill to schedule the automatic run of the jupyter notebook. The details on how to install and run papermill are mentioned in the Jupyter notebook itself.
snigdhakakkar/Custom_Object_Detection
TensorFlow Object Detection
snigdhakakkar/ds-projects
snigdhakakkar/DS_Challenge
Shopify DS Challenge
snigdhakakkar/Face_Recognition_App
Devised a Face Recognition App Using: 1. Flask Web Framework 2. Haarcascades xml files for facial features 3. CSS Stylesheet 4. OpenCV, Numpy, FaceRecognition, Render_template, Response, Url_for Modules from Python 5. Python language for coding
snigdhakakkar/Face_Recognition_Using_TransferLearning_Vgg16-Resnet
Implemented Transfer Learning using State Of Art Models of CNN (Vgg16, Resnet)
snigdhakakkar/Fake-News-Classifier
Implementing Fake news Classifier Using LSTM
snigdhakakkar/Fashion-MNIST---CNN-Implementation-And-Optimization
Convolutional Neural Network Implementation and Optimization Using Keras_tuner in Google Colab
snigdhakakkar/Generative-AI-NLP-Playground
Hands On Practice Code in addition to Generative AI YouTube Playlist for learners
snigdhakakkar/HeartDiseaseDetectionUsingKNN
heart disease detection using K Nearest Neighbor (KNN) algorithm
snigdhakakkar/House_Price_Predictor
Steps Implemented: 79 initial features Technologies: Python, NLTK, Keras, Scikit-learn, pandas, Numpy Pre-processed the raw data, handled the missing values and applied feature engineering Used hyperparameter optimization techniques to find the optimum parameters Predicted Sale Prices to minimize the Cost function using Machine learning Regression models & Neural Networks Explored Linear regression with regularization methods (Ridge, LASSO etc.) & XgBoost Model using scikit-learn
snigdhakakkar/Image_Classification_Using_DeepLearning
Image classification Model Using Vgg19 (Transfer Learning) and implementing it on Flask web framework
snigdhakakkar/ML_Algo_Implementation
Machine Learning Algo Implementation Python for Interviews
snigdhakakkar/Plotly_Tutorial
Interactive charts using Plotly
snigdhakakkar/python-tutorials
snigdhakakkar/Sentiment_Analysis_Engine
Classification of movie reviews using Rule-based and ML Naive Bayes classifiers
snigdhakakkar/Stock-Price-Prediction
Stock Price Prediction and Forecasting Using Stacked LSTM
snigdhakakkar/Transfer-Learning-Using-AlexNet