
Machine learning
46 boardsKiCad boards from 21 GitHub repositories tagged “machine-learning”, the most starred first; open any of them in PCBKit.
- 2 layers15.2 × 10 mm

- 2 layers14 × 12.5 mm

- 2 layers20 × 20 mm

Bistable oscillator with 555 timer and ldo 2lyr setup 00
LukeVassallo/RL_PCB
RL_PCB is a novel learning-based method for optimising the placement of circuit components on a Printed Circuit Board (PCB).
6 parts76MIT - 2 layers20 × 20 mm

PModBoard
LukeVassallo/RL_PCB
RL_PCB is a novel learning-based method for optimising the placement of circuit components on a Printed Circuit Board (PCB).
5 parts76MIT - 2 layers20 × 20 mm

Tc logger max232
LukeVassallo/RL_PCB
RL_PCB is a novel learning-based method for optimising the placement of circuit components on a Printed Circuit Board (PCB).
5 parts76MIT - 2 layers20 × 20 mm

Tc logger max31856
LukeVassallo/RL_PCB
RL_PCB is a novel learning-based method for optimising the placement of circuit components on a Printed Circuit Board (PCB).
8 parts76MIT - 2 layers20 × 20 mm

Tc logger mcu
LukeVassallo/RL_PCB
RL_PCB is a novel learning-based method for optimising the placement of circuit components on a Printed Circuit Board (PCB).
4 parts76MIT - 2 layers20 × 20 mm

Tc logger silabs
LukeVassallo/RL_PCB
RL_PCB is a novel learning-based method for optimising the placement of circuit components on a Printed Circuit Board (PCB).
8 parts76MIT - 2 layers20 × 20 mm

Voltage datalogger adc2
LukeVassallo/RL_PCB
RL_PCB is a novel learning-based method for optimising the placement of circuit components on a Printed Circuit Board (PCB).
3 parts76MIT - 2 layers20 × 20 mm

Voltage datalogger afe
LukeVassallo/RL_PCB
RL_PCB is a novel learning-based method for optimising the placement of circuit components on a Printed Circuit Board (PCB).
9 parts76MIT - 2 layers92.5 × 41.3 mm

Button panel
Tai-Min/Statek-UAV
ROS based UAV (Unmanned Autonomous Vehicle), Master's degree final project
36 parts6MIT - 2 layers39.9 × 40 mm

Enkoder
Tai-Min/Statek-UAV
ROS based UAV (Unmanned Autonomous Vehicle), Master's degree final project
21 parts6MIT - 2 layers120 × 27.3 mm

Keyboard rev0
elcruzo/learned-pcb-placement
GNN-guided simulated annealing for PCB component placement. We train a Graph Attention Network on SA rollout data to learn which components to move and where, then use these predictions to bias the SA search.
37 parts2MIT - 2 layers87.6 × 30.5 mm

Mmdvm hotspot
elcruzo/learned-pcb-placement
GNN-guided simulated annealing for PCB component placement. We train a Graph Attention Network on SA rollout data to learn which components to move and where, then use these predictions to bias the SA search.
21 parts2MIT - 2 layers25.9 × 17.3 mm

Snapvcc
elcruzo/learned-pcb-placement
GNN-guided simulated annealing for PCB component placement. We train a Graph Attention Network on SA rollout data to learn which components to move and where, then use these predictions to bias the SA search.
26 parts2MIT - 2 layers71.4 × 74.4 mm

- 4 layers53.9 × 62.3 mm

Classification and Contol Board
sparkerBCI/FYP
Brain Computer Interface 3-D Printed Prosthetic Hand
94 parts1 - 2 layers50 × 42.7 mm

- 2 layers27.6 × 67.3 mm

- 2 layers109.2 × 66.3 mm

- 2 layers78 × 72 mm

- 2 layers68.6 × 53.3 mm

SAPI LoRa Arduino Shield V1.0
alexandreberg/SAPI_an_open_source_FEWS
Open-source flood early warning system: LoRa water-level and rain stations, gateway, web dashboard and LightGBM/MLR forecasts. Master's dissertation (IFSC, Brazil).
35 partsAGPL-3.0