Abid Ali Awan
kingabzpro
I am certified data scientist professional who loves building machine learning models and write blogs on the AI technologies. My vision is to build an AI product that will identify students struggling with mental illness.
kingabzpro
I am certified data scientist professional who loves building machine learning models and write blogs on the AI technologies. My vision is to build an AI product that will identify students struggling with mental illness.
kingabzpro
I am certified data scientist professional who loves building machine learning models and write blogs on the AI technologies. My vision is to build an AI product that will identify students struggling with mental illness.
Updated 1 year ago
Yoga Pose classification with DagsHub streaming.
dataset model computer vision image classification dvc git mlflow
Open Source Data Science (OSDS) Monocular Depth Estimation – Turn 2d photos into 3d photos – show your grandma the awesome results.
dataset model computer vision pytorch image generation dvc git
Updated 1 year ago
Automatic Speech Recognition using Facebook wav2vec2-xls-r-300m model and mozilla-foundation common_voice_8_0 Urdu Dataset
A demo of the DagsHub <> New Relic integration
Updated 2 years ago
Flask API to predict daily radiation from the time series of Solcast from Islamabad, Pakistan.
Classifying chest X-Ray images for Pneumonia
dataset model medical imaging tensorflow image classification
A showcase for annotations, Label Studio, discussions and related features
No topics have been added
Updated 2 years ago
🤖💬 Transformer TTS: Implementation of a non-autoregressive Transformer based neural network for text to speech.
Designing your first machine learning pipeline with few lines of codes and simple drag and drop using Orchest. In this project we will train binary classification model to predict epitope which is used for vaccine development.
Design your first machine learning pipeline using simple steps on Orchest cloud.
Updated 2 years ago
In this project, we will be using data analysis tools to figure out trends in digital learning and how it is effective towards improvised communities. We will be comparing districts and states on factors like demography, internet access, learning product access, and finance.