8 Deep Learning Frameworks You Must Know in 2022! π₯³
Deep Learning fanatic? Want to build your own neural networks or use the power of transfer learning to utilise the existing ones? Here we have a list of the most well documented, supported and valuable deep learning frameworks! π
π TensorFlow: Developed by the team at Google Brain, this is the most popular framework for building neural networks. Ease of abstraction, scalability and integration with apps makes it one of the easiest choices!Β
π Keras: This user-friendly and open-source library is perfect for research as it offers simple APIs, modularity and extensibility.
π PyTorch: This amazing framework offers scalable distributed training and performance optimization in research and production using the βtorch distributedβ backend.
π Theano: This framework has tight integration with NumPy and is centred around the CUDA cores offered by NVIDIA.Β
π DeepLearning4j: This framework is recommended for Java, Scala, C++ and C users. It is best known for distributed training which happens in clusters.
π Caffe: Caffe is written in C++ with a Python Interface and is generally used for image detection and classification.Β
π Chainer: Written purely in Python, it is best known for running on multiple GPUs with little effort.
π Microsoft CNTK: Designed for speed and efficiency, this framework builds a neural network as a series of computational steps via a direct graph.
For more details about these frameworks, check out the source article at https://www.simplilearn.com/tutorials/deep-learning-tutorial/deep-learning-frameworks
Here's the curriculum for our upcoming Project-Based Deep Learning Bootcamp starting 12th of February! π
β³ Only 8 seats remaining! Get yourselves registered soon: https://www.townscript.com/e/project-based-deep-learning-bootcamp-322021
The first few registrants get a flat 10% off using the 'MLIDL10' coupon code! π