GitHub - facebookresearch/Detectron: FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.You signed in with another tab or window. Reload to refresh your session. You signed out in another tab or window. Reload to refresh your session. You switched accounts on another tab or window. Reload to refresh your session. Dismiss alert
deep-learning-book/README.md at master · rasbt/deep-learning-book
Machine learning has become a central part of our life — as consumers, customers, and hopefully as researchers and practitioners! I appreciate all the nice feedback that you sent me about Python Machine Learning, and I am so happy to hear that you found it so useful as a learning guide, helping you with your business applications and research projects. I have received many emails since its release
GitHub - DT42/BerryNet: Deep learning gateway on Raspberry Pi and other edge devices
This project turns edge devices such as Raspberry Pi into an intelligent gateway with deep learning running on it. No internet connection is required, everything is done locally on the edge device itself. Further, multiple edge devices can create a distributed AIoT network. At DT42, we believe that bringing deep learning to edge devices is the trend towards the future. It not only saves costs of d
GitHub - BilalReffas/EmojiIntelligence: Neural Network built in Apple Playground using Swift
I used this challenge to learn more about neural networks and machine learning. A neural network consists of layers, and each layer has neurons. My network has three layers: an input layer, a hidden layer, and an output layer. The input to my network has 64 binary numbers. These inputs are connected to the neurons in the hidden layer. The hidden layer performs some computation and passes the resul
kaggle_memo/README.md at master · nejumi/kaggle_memo
まずは、素うどんのXGBoostにかけて、plot_importance, feature_importances_を確認する。しかる後に、各特徴量をF-SCOREの高い順にExploratory Data Analysis (EDA)を行い、データに対する感覚を掴む。特徴量の数が少ないのであれば、初めからEDA。 情報を含まないcolumnsを除く。[Kaggle Kernel: R, Python] 標準偏差が0の説明変数 (constant cols) を除く。 重複した説明変数 (duplicated cols) を1つだけ残して他を除く。 相関係数が1である説明変数の組 (perfectly correlated cols) を探し、1つだけ残して他を除く。 各列について、値が0である説明変数の数を数えて、合計値を追加の説明変数として加える (count 0 per row)。逆
GitHub - nejumi/kaggle_memo
まずは、素うどんのXGBoostにかけて、plot_importance, feature_importances_を確認する。しかる後に、各特徴量をF-SCOREの高い順にExploratory Data Analysis (EDA)を行い、データに対する感覚を掴む。特徴量の数が少ないのであれば、初めからEDA。 情報を含まないcolumnsを除く。[Kaggle Kernel: R, Python] 標準偏差が0の説明変数 (constant cols) を除く。 重複した説明変数 (duplicated cols) を1つだけ残して他を除く。 相関係数が1である説明変数の組 (perfectly correlated cols) を探し、1つだけ残して他を除く。 各列について、値が0である説明変数の数を数えて、合計値を追加の説明変数として加える (count 0 per row)。逆
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GitHub - Netflix/vectorflow
GitHub - tensorflow/tfjs-core: WebGL-accelerated ML // linear algebra // automatic differentiation for JavaScript.
GitHub - minimaxir/textgenrnn: Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.
GitHub - red-data-tools/red-chainer: A flexible framework for neural network for Ruby
GitHub - rasbt/deep-learning-book: Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"
GitHub - mdipierro/nlib: The book "Annotated Algorithms in Python" and the nlib.py library
GitHub - ArunMichaelDsouza/tensorflow-image-detection: A generic image detection program that uses Google's Machine Learning library, Tensorflow and a pre-trained Deep Learning Convolutional Neural Network model called Inception.
GitHub - tonybeltramelli/pix2code: pix2code: Generating Code from a Graphical User Interface Screenshot
GitHub - intel/clDNN: Compute Library for Deep Neural Networks (clDNN)
GitHub - sbrugman/deep-learning-papers: Papers about deep learning ordered by task, date. Current state-of-the-art papers are labelled.
GitHub - aditya1503/Siamese-LSTM: Siamese Recurrent Neural network with LSTM for evaluating semantic similarity between sentences.
GitHub - google-deepmind/sonnet: TensorFlow-based neural network library
Qiita_Contents/General/Decision_tree.ipynb at master · matsuken92/Qiita_Contents
GitHub - openfaas/faas: OpenFaaS - Serverless Functions Made Simple
