| BMW-InnovationLab/BMW-TensorFlow-Training-GUI |
954 |
|
0 |
0 |
over 2 years ago |
0 |
|
0 |
apache-2.0 |
Python |
| This repository allows you to get started with a gui based training a State-of-the-art Deep Learning model with little to no configuration needed! NoCode training with TensorFlow has never been so easy. |
| somaticio/tensorflow.rb |
828 |
|
0 |
0 |
over 4 years ago |
0 |
|
14 |
bsd-3-clause |
Ruby |
| tensorflow for ruby |
| torrvision/crayon |
772 |
|
0 |
0 |
over 8 years ago |
0 |
|
17 |
mit |
Python |
| A language-agnostic interface to TensorBoard |
| google-research/seed_rl |
755 |
|
0 |
0 |
over 3 years ago |
0 |
|
22 |
apache-2.0 |
Python |
| SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference. Implements IMPALA and R2D2 algorithms in TF2 with SEED's architecture. |
| BMW-InnovationLab/BMW-YOLOv4-Training-Automation |
630 |
|
0 |
0 |
almost 3 years ago |
0 |
|
9 |
bsd-3-clause |
Python |
| This repository allows you to get started with training a state-of-the-art Deep Learning model with little to no configuration needed! You provide your labeled dataset or label your dataset using our BMW-LabelTool-Lite and you can start the training right away and monitor it in many different ways like TensorBoard or a custom REST API and GUI. NoCode training with YOLOv4 and YOLOV3 has never been so easy. |
| 30lm32/ml-projects |
232 |
|
0 |
0 |
over 5 years ago |
0 |
|
|
|
|
| ML based projects such as Spam Classification, Time Series Analysis, Text Classification using Random Forest, Deep Learning, Bayesian, Xgboost in Python |
| martinwicke/tensorflow-tutorial |
225 |
|
0 |
0 |
over 9 years ago |
0 |
|
1 |
apache-2.0 |
Jupyter Notebook |
| A tutorial on TensorFlow |
| mimoralea/applied-reinforcement-learning |
219 |
|
0 |
0 |
over 5 years ago |
0 |
|
2 |
mit |
Jupyter Notebook |
| Reinforcement Learning and Decision Making tutorials explained at an intuitive level and with Jupyter Notebooks |
| zcemycl/TF2DeepFloorplan |
107 |
|
0 |
0 |
almost 3 years ago |
0 |
|
2 |
gpl-3.0 |
Python |
| TF2 Deep FloorPlan Recognition using a Multi-task Network with Room-boundary-Guided Attention. Enable tensorboard, quantization, flask, tflite, docker, github actions and google colab. |
| wagonhelm/TF_ObjectDetection_API |
105 |
|
0 |
0 |
almost 8 years ago |
0 |
|
4 |
|
Jupyter Notebook |
| Tutorial on how to create your own object detection dataset and train using TensorFlow's API |
