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Deep Learning Frameworks in 2025: A Review
Manage episode 461829787 series 3620285
Вміст надано David Such. Весь вміст подкастів, включаючи епізоди, графіку та описи подкастів, завантажується та надається безпосередньо компанією David Such або його партнером по платформі подкастів. Якщо ви вважаєте, що хтось використовує ваш захищений авторським правом твір без вашого дозволу, ви можете виконати процедуру, описану тут https://uk.player.fm/legal.
In this episode, we investigate the state of deep learning frameworks in 2025. We review the leading contenders—TensorFlow, PyTorch, JAX, MXNet, and LightningAI—analyzing their strengths, latest features, performance benchmarks, and the size of their user communities.
We also explore key trends shaping the field, including the sustained dominance of established frameworks and the growing popularity of specialized options like LightningAI, known for its focus on performance, scalability, and usability. To wrap up, we discuss future directions in deep learning frameworks, from integrating quantum computing to improving model interpretability. Tune in for a forward-looking discussion on the tools driving the future
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