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Accuracy and Loss
Activation Function
AI Chips for Training and Inference
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Comparison of ML Frameworks
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Containers
Convergence
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Data Science vs Machine Learning vs Deep Learning
Datasets and Machine Learning
Distributed Training (TensorFlow, MPI, & Horovod)
Epochs, Batch Size, & Iterations
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Generative Adversarial Network (GAN)
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Overfitting vs Underfitting
Random Forest
Recurrent Neural Network (RNN)
Reproducibility in Machine Learning
REST and gRPC
Serverless ML: FaaS and Lambda
Structured vs Unstructured Data
Supervised, Unsupervised, & Reinforcement Learning
Synthetic Data
Tensor Processing Unit (TPU)
TensorBoard
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