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100-pandas-puzzles

100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)

365-days-computer-vision-learning-linkedin-post

365 Days Computer Vision Learning Linkedin Post

adv_tf

advanced-deep-learning-with-keras

Advanced Deep Learning with Keras, published by Packt

all-cell-classification

The proposed hybrid convolutional neural network architecture is a neural network architecture consisting of a combination of the VGG16, ResNet50, InceptionV3, and the DenseNet121 architectures, all of which have been pretrained on the ImageNet database. The purpose of this model is to identify if an image of a cell has acute lymphocytic leukemia (also referred to as ALL), or if it is a healthy cell. The dataset used contains 1700 images from the training set of the ALL Challenge dataset of ISBI 2019 (which is available here). Of those 1700 images, there were an equal number of images with healthy cells and images with ALL cells. 60% of those images were used to train the model, 20% of those images were used for the cross validation set, and 20% of those images were used for the test set. The model used in the study generally outperformed the VGG16, ResNet50, and the InceptionV3 models on the cross validation set, in which it achieved an accuracy of 92.35%, a sensitivity of 0.927, a specificity of 0.918, and an F1 score of 0.932. The goal of this study was to verify that the developed algorithm could be utilized by hospitals and doctors to better treat the thousands of people suffering with ALL across the world, many of whom are children.

andrew-ng-notes

This is Andrew NG Coursera Handwritten Notes.

application_of_fft_with_fir_filter

This project will walk you through the importance of Fast Fourier Transform (FFT) which is one of the major computation techniques in the world of Digital Signal Processing (DSP). It also explains how 'Filter Design Toolbox' can be made use of in MATLAB to design desired filters on the go.

applied-deep-learning-with-keras

Deep Learning examples with Keras.

applied-ml

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

audio-visual-cryptography-using-aes-rsa

audiosignalprocessingforml

Code and slides of my YouTube series called "Audio Signal Proessing for Machine Learning"

awesome

😎 Awesome lists about all kinds of interesting topics

awesome-deep-learning

A curated list of awesome Deep Learning tutorials, projects and communities.

awesome-rnn

Recurrent Neural Network - A curated list of resources dedicated to RNN

binary-search-tree-in-java

Binary Search Tree in Java, written about 2 years ago.

bone-age-assessment

Bone Age Assessment；Keras

book_scrap_trial1

canvas-experiments

Some experiments using Canvas HTML5 technology.

chexnet-pytorch

Solving CheXNet using a DenseNet121 in Pytorch

coursera-deep-learning-specialization

Notebooks for Coursera Deep Learning Specialization

cs231n.github.io

Public facing notes page

data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

deep-learning-for-hackers

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

deep-learning-papers-reading-roadmap

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

deep-learning-time-series

List of papers, code and experiments using deep learning for time series forecasting

deeplearning

A collection of research papers, datasets and software on Deep Learning

detecto

Build fully-functioning computer vision models with PyTorch

dl-4-tsc

Deep Learning for Time Series Classification

dsp_proj

email-form-nodejs