Kamanda Wycliffe - Machine learning nuggets

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Kamanda Wycliffe

Data Scientist and Ethical Hacker with interest in data modeling and data-driven cyber security systems.

Gradio tutorial (Build machine learning applications)

Gradio tutorial (Build machine learning applications)

You have built your optimally performing machine learning model. What next? This tutorial explores the use of Gradio in building machine learning applications. What is Gradio? Gradio is an open-source Python package that allows you to quickly create easy-to-use, customizable UI components for your ML model, any API, or even

Transfer learning guide(With examples for text and images in Keras and PyTorch)

Transfer learning guide(With examples for text and images in Keras and PyTorch)

Training computer vision (CV) or natural language processing (NLP) models can be expensive and requires large datasets. If labeling is done manually, the process will take a longer training time and requires expensive hardware. For instance, the Generative Pre-trained Transformer 2 (GPT-2), a benchmark-setting language model created by Open AI

TensorBoard tutorial (Deep dive with examples and notebook)

TensorBoard tutorial (Deep dive with examples and notebook)

TensorBoard is a visualization library that enables data science practitioners to visualize various aspects of their machine learning modeling. For instance, you can use TensorBoard to: * Visualize the performance of the model. * Tuning model parameters. * Profile the executions of the program. For example, check the utilization of GPUs. * Debug machine

Streamlit tutorial(How to build
machine learning applications)

Data Science Featured

Streamlit tutorial(How to build machine learning applications)

Data science deals with large volumes of data using modern tools and methods to extract hidden patterns, obtain meaningful information, and inform business decisions. The application of data science in business, education, and economics has led to the emergence of various tools. Applying data science requires understanding the main components