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deathnote

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

deeplearning-project

DeepLearning Projects

deeplearning.ai-assignments

deeplearningforaudiowithpython

Code and slides for the "Deep Learning (For Audio) With Python" course on TheSoundOfAI Youtube channel.

denoising-autoencoder-in-pytorch

A Pytorch Implementation of a denoising autoencoder.

dicom2mesh

A simple Python script which utilises marching cubes algorithm(skimage library) to generate 3D mesh from Dicom/Nifti image stack, which then can be output to .obj file.

dlvc2017ws

dlvcnptel

Tutorials for DLVC NPTEL MOOC

docker_try

enodo---2020

explainable-cnn

📦 PyTorch based visualization package for generating layer-wise explanations for CNNs.

fastbook

The fastai book, published as Jupyter Notebooks

financial-documents-ocr-deep-learning

freelance_ml

freeml

Data Science Resources (Mostly Free)

from-0-to-research-scientist-resources-guide

Detailed and tailored guide for undergraduate students or anybody want to dig deep into the field of AI with solid foundation.

getting-started-with-google-bert

Build and train state-of-the-art natural language processing models using BERT

github-profile-summary-cards

A tool to generate your github summary card for profile README

hactoberfest2020

Submit 4 pull requests to earn swags (Tshirts + badges)

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

hello-world

Yo guys. This is my first repository file in github. Wish me luck

ibm_watson_speech_to_text

Leveraging the services of IBM Watson to convert the Real-Time Input Speech to Text

image_compression

Image Compression Algorithm

image_to_image_search

quick tinkering on learning how CLIP generates image embeddings and using it to find similar images

intelligent-travel-recommendation-system

The project provides a Tailor-made travel itinerary for users using their travel details like destination, budget, start and end dates of travel and their preferences of attraction categories, hotel amenities and cuisine type. Our project significantly reduces the time spent on planning for a satisfactory vacation.

introtodeeplearning

Lab Materials for MIT 6.S191: Introduction to Deep Learning

ipl-web-project

jalammar.github.io

Build a Jekyll blog in minutes, without touching the command line.

kaggle_titanic

I have uploaded both the answer as well as the code for (THE TITANIC KAGGLE QUES) it using scikit learn , and pandas(ML)