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  1. Hace 5 días · Get to know the top 10 Deep Learning Algorithms with examples such as ️CNN, LSTM, RNN, GAN, & much more to enhance your knowledge in Deep Learning. Read on!

    • DBN

      If you're looking for a new way to generate data, consider...

    • GANs

      Deep Learning has found numerous applications in the...

    • Deep Learning Interview Questions

      The demand for Deep Learning has grown over the years and...

  2. Hace 5 días · Pipeline parallelism improves both the memory and compute efficiency of deep learning training by partitioning the layers of a model into stages that can be processed in parallel. DeepSpeed’s training engine provides hybrid data and pipeline parallelism and can be further combined with model parallelism such as Megatron-LM.

  3. Hace 5 días · DeepSpeed provides a seamless inference mode for compatible transformer based models trained using DeepSpeed, Megatron, and HuggingFace, meaning that we don’t require any change on the modeling side such as exporting the model or creating a different checkpoint from your trained checkpoints.

  4. Hace 5 días · The details of BERT can be found here: BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. We will go through how to setup the data pipeline and how to run the original BERT model. Then we will show step-by-step how to modify the model to leverage DeepSpeed.

  5. Hace 5 días · Introduction. Ever wondered how machines can recognize your face in photos or translate languages in real-time? That’s the magic of neural networks! In this blog, we’ll dive into the different types of neural networks used in deep learning.

  6. Hace 2 días · How to run deep networks in browser. Custom deep learning layers support. How to run custom OCR model. High Level API: TextDetectionModel and TextRecognitionModel. DNN-based Face Detection And Recognition. PyTorch models with OpenCV.

  7. Hace 5 días · Introduction. The various deep learning methods use data to train neural network algorithms to do a variety of machine learning tasks, such as the classification of different classes of objects. Convolutional neural networks are deep learning algorithms that are very powerful for the analysis of images.