adijindal30
Machine Learning Engineer by training and a keen reader by heart. I love computer vision in many ways.
Pinned Repositories
Big-Data-Analysis-Dask-df
The dataset is tabular and the features involved should be self-explanatory. We would like for you to come up with a specific problem yourself and solve it properly. This is an “open challenge,” mainly focusing on natural language processing. The problem could be either about predictive modeling or providing analytical insights for some business use cases. Note the problem should be treated as large-scale, as the dataset is large (e.g., >100GB) and will not fit into the RAM of your machine. Python is strongly recommended in terms of the coding language.
Car-Engine-Rating-Prediction-ML-Model
datasciencecoursera
Data Science Repo and blog for John Hopkins Coursera Courses. Please let me know if you have any questions.
dlib
A toolkit for making real world machine learning and data analysis applications in C++
mnist
Python utilities to download and parse the MNIST dataset
MNIST-Digit-recognition-using-DNN
Stock-Market-Predictions-using-Global-News-Sentiment
Table-Fact-Checking
Data and Code for ICLR2020 Paper "TabFact: A Large-scale Dataset for Table-based Fact Verification"
Imbalanced-Speaker-Diarization
TablEval
adijindal30's Repositories
adijindal30/Big-Data-Analysis-Dask-df
The dataset is tabular and the features involved should be self-explanatory. We would like for you to come up with a specific problem yourself and solve it properly. This is an “open challenge,” mainly focusing on natural language processing. The problem could be either about predictive modeling or providing analytical insights for some business use cases. Note the problem should be treated as large-scale, as the dataset is large (e.g., >100GB) and will not fit into the RAM of your machine. Python is strongly recommended in terms of the coding language.
adijindal30/Car-Engine-Rating-Prediction-ML-Model
adijindal30/mnist
Python utilities to download and parse the MNIST dataset
adijindal30/MNIST-Digit-recognition-using-DNN
adijindal30/Table-Fact-Checking
Data and Code for ICLR2020 Paper "TabFact: A Large-scale Dataset for Table-based Fact Verification"
adijindal30/datasciencecoursera
Data Science Repo and blog for John Hopkins Coursera Courses. Please let me know if you have any questions.
adijindal30/dlib
A toolkit for making real world machine learning and data analysis applications in C++
adijindal30/Stock-Market-Predictions-using-Global-News-Sentiment
adijindal30/MobileNetV2-dynamicFPN
MobileNetV2 architecture combined with a dynamically generated Feature Pyramid Network
adijindal30/PAN.pytorch
A unofficial pytorch implementation of PAN(PSENet2): Efficient and Accurate Arbitrary-Shaped Text Detection with Pixel Aggregation Network
adijindal30/pytorch-mobilenet-v3
MobileNetV3 in pytorch and ImageNet pretrained models
adijindal30/pytorchTutorial
PyTorch Tutorials from my YouTube channel
adijindal30/segmentation_models.pytorch
Segmentation models with pretrained backbones. PyTorch.
adijindal30/vision
Datasets, Transforms and Models specific to Computer Vision