#cplusplus #cuda #deep_learning #deep_neural_networks #distributed #machine_learning #ml #neural_network

https://github.com/Oneflow-Inc/oneflow

#jupyter_notebook #cnn #colab #colab_notebook #computer_vision #deep_learning #deep_neural_networks #fourier #fourier_convolutions #fourier_transform #gan #generative_adversarial_network #generative_adversarial_networks #high_resolution #image_inpainting #inpainting #inpainting_algorithm #inpainting_methods #pytorch

https://github.com/saic-mdal/lama

#other #classification #convolutional_neural_networks #dataset #datasets #deep_learning #deep_neural_networks #image_classification #keras #machine_learning #python #pytorch #remote_sensing #satellite_data #satellite_imagery #satellite_images #sentinel #tensorflow

https://github.com/robmarkcole/satellite-image-deep-learning

#cplusplus #android #asr #deep_learning #deep_neural_networks #deepspeech #google_speech_to_text #ios #kaldi #offline #privacy #python #raspberry_pi #speaker_identification #speaker_verification #speech_recognition #speech_to_text #speech_to_text_android #stt #voice_recognition #vosk

https://github.com/alphacep/vosk-api

#jupyter_notebook #andrew_ng #andrew_ng_course #andrew_ng_machine_learning #andrewng #coursera #coursera_machine_learning #data_science #deep_learning #deep_neural_networks #dl #machine_learning #ml #neural_network #neural_networks #numpy #pandas #python #pytorch #reinforcement_learning

https://github.com/ashishpatel26/Andrew-NG-Notes

#jupyter_notebook #computer_vision #deep_learning #deep_neural_networks #image_classification #image_segmentation #object_detection #pytorch #tutorial #yolov5 #yolov6 #yolov7

https://github.com/roboflow-ai/notebooks

#cplusplus #caffe #convolution #deep_learning #deep_neural_networks #diy #graph_algorithms #inference #inference_engine #maxpooling #ncnn #pnnx #pytorch #relu #resnet #sigmoid #yolo #yolov5

This course, "_动手自制大模型推理框架_" (Handcrafting Large Model Inference Framework), is a valuable resource for those interested in deep learning and model inference. It teaches you how to build a modern C++ project from scratch, focusing on designing and implementing a deep learning inference framework. The course supports latest models like LLama3.2 and Qwen2.5, and uses CUDA acceleration and Int8 quantization for better performance.

By taking this course, you will learn how to write efficient C++ code, manage projects with CMake and Git, design computational graphs, implement common operators like convolution and pooling, and optimize them for speed. This knowledge will be highly beneficial for job interviews and advancing your skills in deep learning. The course also includes practical demos on models like Unet and YoloV5, making it a hands-on learning experience.

https://github.com/zjhellofss/KuiperInfer

#cplusplus #deep_learning #deep_neural_networks #distributed #machine_learning #ml #neural_network #python #tensorflow

TensorFlow is a powerful tool for machine learning that helps you build and deploy AI applications easily. It was developed by Google and is now open source, meaning anyone can use and contribute to it. TensorFlow provides tools, libraries, and a strong community to support your work. You can install it using Python with a simple command like `pip install tensorflow`, and it supports various devices including GPUs. This makes it versatile for researchers and developers alike, allowing you to push the boundaries of machine learning and create innovative applications.

https://github.com/tensorflow/tensorflow

#jupyter_notebook #ai #computer_vision #computervision #deep_learning #deep_neural_networks #deeplearning #machine_learning #opencv #opencv_cpp #opencv_library #opencv_python #opencv_tutorial #opencv3

Learning OpenCV and AI can greatly benefit your career by opening up opportunities in fields like autonomous vehicles, healthcare, and robotics. OpenCV University offers comprehensive courses that teach computer vision and deep learning using frameworks like PyTorch. These courses are project-based, providing hands-on experience with real-world applications. By mastering these skills, you can develop innovative solutions and even start your own AI company. The courses are accessible to beginners and offer lifetime access for continuous learning.

https://github.com/spmallick/learnopencv

#jupyter_notebook #cnn #colab #colab_notebook #computer_vision #deep_learning #deep_neural_networks #fourier #fourier_convolutions #fourier_transform #gan #generative_adversarial_network #generative_adversarial_networks #high_resolution #image_inpainting #inpainting #inpainting_algorithm #inpainting_methods #pytorch

LaMa is a powerful tool for removing objects from images. It uses special techniques called Fourier Convolutions, which help it understand the whole image at once. This makes it very good at filling in large areas that are missing. LaMa can even work well with high-resolution images, even if it was trained on smaller ones. This means you can use it to fix photos where objects are in the way, making them look natural and complete again.

https://github.com/advimman/lama

#jupyter_notebook #android #asr #deep_learning #deep_neural_networks #deepspeech #google_speech_to_text #ios #kaldi #offline #privacy #python #raspberry_pi #speaker_identification #speaker_verification #speech_recognition #speech_to_text #speech_to_text_android #stt #voice_recognition #vosk

Vosk is a powerful tool for recognizing speech without needing the internet. It supports over 20 languages and dialects, making it useful for many different users. Vosk is small and efficient, allowing it to work on small devices like smartphones and Raspberry Pi. It can be used for things like chatbots, smart home devices, and creating subtitles for videos. This means users can have private and fast speech recognition anywhere, which is especially helpful when internet access is limited.

https://github.com/alphacep/vosk-api