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In this repository, I will share some useful notes and references about deploying deep learning-based models in production.
A best practice for tensorflow project template architecture.
tensorflow implementation of Grad-CAM (CNN visualization)
📖 👆🏻 Links Detector makes printed links clickable via your smartphone camera. No need to type a link in, just scan and click on it.
Google Street View House Number(SVHN) Dataset, and classifying them through CNN
Learn to design, develop, train, and deploy TensorFlow and Keras models as real-world applications
Showing full TensorBoard support in Tensorflow for a CNN using MNIST data.
SEQ2SEQ model with Attention mechanism for QA also for NMT +(Generating text using LSTM network)
Discord Bot in python with rasa nlu, tensorflow, discord api
The fully connected neural network implemented in Numpy, from scratch, in Tensorflow and in Keras. The bonus code: Implementation of many different activation functions, in python, weight inits.
Pseudo Labelling on MNIST dataset in Tensorflow 2.x
Deep learning for image classification via transfer learning using Keras, PyTorch, and MXNet on Cloudera Data Science Workbench
Models, and associated helper code for GSOC 2017 project Tensorflow Image to Text in Apache Tika
Making mosaic art of a given image using tile images generated by a Stable Diffusion model using KerasCV
In this Project we aim to dive into a Present Societal Pandemic issue which we are facing around us past 2 years due to outbreak of Novel Corona Virus. Getting tested for covid-19 virus is not an easy deal with costly RT-PCR test, and delayed results, and with its no. of variants with different mutations emerging everyday all the new methods found to detect the virus and its variant have either become : - Ineffective as all tests may not find each of the variants. - Each of them a set a finical restrictions for the technology used. - Each test has its own detection time . Chest X-Ray already exists and overcomes most of the above drawbacks, but still fail to give long term effects or severity. So as a Solution We Aim to develop a model to give large no. of classifications and comparisons of Covid Patients and whether it leads to pneumonia disease , also these models could be trained to classify long term effects after years of infection how things could change w.r.t chest infections, and lead to other chronic disease.
Original Keras implementation of the code for the paper "Client-driven animated GIF generation framework using an acoustic feature," at 1171: Real-time 2D/3D Image Processing with Deep Learning (MTAP)
:fire: Deep NN Models with FRAMEWORKS -- PyTorch, Tensorflow 2, Kaldi, FastSpeech, MxNET Frameworks -- Image/Speech/NLP/Recommendation/Transformer Cognitive Analytics
deep learning chat bot using Keras , NLP
Course work of Computational physics
Here i have done CFD Simulation of Airfoil using Ansys ( commercial cfd software ) and OpenFoam (opensource software).
Predict the digit
Limited Keyword Speech Recognition using Transfer Learning
A Command Line Tool (or CLI) to perform Neural Style Transfer along with image filtering to produce an artistic recreation of an input image!
Computer Vision Game Based on Tensorflow.js and MNIST recognition Model
To test if CAPTCHA secure login security codes are secure from bot attacks I developed a CNN classifier model in Python using TensorFlow to predict the CAPTCHA codes. Predicted over 40,000 CAPTCHA codes with an accuracy above 98%.
Cars detecting and counting using OpenCV
Speech Recognition is an important feature in several applications used such as home automation, artificial intelligence, etc. This article aims to provide an introduction on how to make use of the SpeechRecognition library of Python. This is useful as it can be used on micro controllers such as Raspberry Pis with the help of an external microphone.
Face Mask Detection system both on image and video based on computer vision and deep learning using OpenCV and Tensorflow/Keras