吴恩达《LLM Agent Fine-Tuning: Enhancing Task Automation with Weights & Biases》中英字幕 01:00:56 吴恩达《FastAPI for Machine Learning: Live coding an ML web application》中英字幕 01:00:07 吴恩达《构建使用抱脸的机器学习应用|Building ML Apps with Hugging Face LLMs to Diffusion Modeling》 01...
deep-learning pytorch image-denoising convolutional-sparse-coding Updated Feb 18, 2023 Python tata1661 / OCSC Star 8 Code Issues Pull requests Code for "Online convolutional sparse coding (TIP 2018)". sparse-coding dictionary-learning convolutional-sparse-coding Updated Jun 1, 2019 MATLA...
1.Hands-On Machine Learning with Scikit-Learn and TensorFlow 本书以实操的形式，通过流行的机器学习...
Building a Hand-Drawn Digit Recognizer with PyTorch and MNIST I trained a neural net to recognize hand-drawn digits, then built a Next.js UI for it May 10, 2024 Build a RAG pipeline for your blog with LangChain, OpenAI and Pinecone ...
Finally, the cosine similarity histograms in Figures 3, 8, and 9 can be generated with generate_prototype_histograms.py. Dependencies The code is written for PyTorch, and requires the usual PyTorch/Torchvision/NumPy family of packages, as well as a few from the Python3 standard library. It ...
There will always be a need for custom solutions and efficient algorithms, tasks that require deep understanding of coding. AI and Machine Learning Artificial intelligence (AI) and machine learning (ML) are already having a significant impact on coding. With tools such as TensorFlow, PyTorch,...
Code Llama (and larger versions 13B, 34B, 70B): It is recommended for code completion and code summarization Code Llama-Python (7B, 13B, 34B, 70B): specializes in Python code generation and understanding. It is particularly useful for developers working with Python and PyTorch. Code Llama-Inst...
(For brevity, and to keep the article focused on the technical self-attention details, and I am skipping parts of the motivation, but myMachine Learning with PyTorch and Scikit-Learn bookhas some additional details in Chapter 16 if you are interested.) ...
[19]. This in-depth evaluation framework not only strengthens the validity of our results but also provides unique insights. When compared against a conventional training procedure with compressed content, results indicate that bitrate savings are achieved for both machine tasks at equivalent machine ...
Pytorch implementation for “Adversarial Learning with Local Coordinate Coding”. Architecture of LCCGAN AutoEncoder (AE) learns embeddings on the latent manifold. Local Coordinate Coding (LCC) learns local coordinate systems. The LCC sampling method is conducted on the latent manifold. ...