A quick refresher into distributed training using tf.distribute.strategy

Need to distribute the model training

  • Training on a single GPU device takes a longer duration compared to training on multiple GPU devices.
  • Current deep learning models are becoming complex, with millions…

Profile and Monitor System Resources in Python using psutil and GPUtil

If you cannot measure it, you cannot improve it- Lord Kelvin

  • CPU
  • Memory -RAM, Swap space, and Hard disk space
  • Network usage
  • GPU usage
Photo by Ibrahim Boran on Unsplash

Learn different deployment strategies for ML solutions to decide which one works best for your use case.

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Build Keras model using mixed and imbalanced data of medical imaging and patient data to determine the presence of Melanoma.

Build deep learning model in Keras using Sequential, Functional Keras API, and Model Subclassing

Keras Sequential Model

Sequential groups a linear stack of layers into…

What are DevOps, MLOps, and AIOps? How do they help organizations with Digital Transformation?

DevOps: Integration of Development, Operation, and Quality Assurance

DevOps collaborates development, quality assurance, and…

Learn the advanced data labeling techniques: Weak Supervision and Active Learning

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  • Why do we need advanced data labeling techniques?
  • What is Active Learning and different types of Active Learning?
  • What is Weak Supervision, and how does it work?
  • Differences between Weak Supervision and Active Learning

Label the unlabelled data using a semi-supervised Label Propagation algorithm

  • What is semi-supervised learning?
  • What is label propagation?
  • How does it work?
  • A Python implementation using sklearn

Semi-Supervised learning is a combination of supervised and unsupervised learning.

A step-by-step explanation and implementation of Vision Transformer using TensorFlow 2.3

Learn hyperparameter tuning for your deep learning models using KerasTuner

  • What are hyperparameters for a deep learning algorithm?
  • Why do we need hyperparameter optimization?
  • Different techniques for hyperparameter optimization like Grid Search, Random Search, Bayesian Optimization, Simulated Annealing, and Hyberband
  • What is KerasTuner, and how does it help with hyperparameter optimization?
  • Implementat hyperparameter optimization…

Renu Khandelwal

Loves learning, sharing, and discovering myself. Passionate about Machine Learning and Deep Learning

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