| martinwicke/tensorflow-tutorial |
225 |
|
0 |
0 |
over 9 years ago |
0 |
|
1 |
apache-2.0 |
Jupyter Notebook |
| A tutorial on TensorFlow |
| shekit/machine-learning-demystified |
114 |
|
0 |
0 |
almost 9 years ago |
0 |
|
0 |
|
Jupyter Notebook |
| A weekly workshop series at ITP to teach machine learning with a focus on deep learning |
| ahundt/robotics_setup |
112 |
|
0 |
0 |
almost 5 years ago |
0 |
|
1 |
apache-2.0 |
Shell |
| Setup Ubuntu 18.04, 16.04 and 14.04 with machine learning and robotics software plus user configuration. Includes ceres tensorflow ros caffe vrep eigen cudnn and cuda plus many more. |
| mwidjaja1/DSOnMacARM |
99 |
|
0 |
0 |
almost 5 years ago |
0 |
|
0 |
mit |
|
| My notes on how I created my Data Science environment on macOS ARM |
| GokuMohandas/attentional-interfaces |
59 |
|
0 |
0 |
over 7 years ago |
0 |
|
0 |
|
Jupyter Notebook |
| 🔍 Attentional interfaces in TensorFlow. |
| akozd/tensorflow_yolo_v3 |
37 |
|
0 |
0 |
over 7 years ago |
0 |
|
6 |
mit |
Python |
| A well-documented TensorFlow implementation of the YOLOv3 model. |
| kumarkan/Food_Detection |
32 |
|
0 |
0 |
over 7 years ago |
0 |
|
3 |
|
Python |
| Food detection using Tensorflow Object Detection API |
| docwire/docwire |
31 |
|
0 |
0 |
about 2 years ago |
0 |
|
2 |
other |
C++ |
| DocWire SDK: Award-winning modern data processing in C++20. SourceForge Community Choice & Microsoft support. AI-driven processing. Supports nearly 100 data formats, including email boxes and OCR. Boost efficiency in text extraction, web data extraction, data mining, document analysis. Offline processing is possible for security and confidentiality |
| parrondo/deeptrading |
30 |
|
0 |
0 |
about 6 years ago |
0 |
|
2 |
mit |
Jupyter Notebook |
| Deep Neural Network Trading collection of Tensorflow Jupyter notebooks |
| TsaiRongFu/AI-Aquaculturing |
18 |
|
0 |
0 |
over 2 years ago |
0 |
|
0 |
mit |
Python |
| This project is developed for smart aquaculture. We use a camera to capture pictures of fishes in the tank. A deep neural network (MobileNet) is applied to recognize the images to identify the situation of fishes in the tank. EdgeTPU is used for edge computing. We also monitor the water quality by some environmental sensors. All the information is integrated into a website constructed by Laravel, and a Linebot is used to deliver information on mobile phones.Four undergraduate students develop this project from the Department of Management Information Systems (MIS), National Pingtung University of Science and Technology (NPUST), Taiwan. |
