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I thought you needed advanced math to build machine learning models, but I was wrong
Machine learning sounds math-heavy, but modern tools make it far more accessible. Here’s how I built models without deep math ...
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Master k-means clustering in Python like a pro
K-means clustering is one of the most approachable unsupervised learning techniques for finding patterns in unlabeled data. With Python’s scikit-learn and pandas, you can prepare, model, and evaluate ...
Scikits are Python-based scientific toolboxes built around SciPy, the Python library for scientific computing. Scikit-learn is an open source project focused on machine learning: classification, ...
A regression problem is one where the goal is to predict a single numeric value. For example, you might want to predict the annual income of a person based on their sex, age, State where they live and ...
TensorFlow, Spark MLlib, Scikit-learn, PyTorch, MXNet, and Keras shine for building and training machine learning and deep learning models. If you’re starting a new machine learning or deep learning ...
Dr. James McCaffrey of Microsoft Research shows how to predict a person's sex based on their job type, eye color and country of residence. Naive Bayes classification is a classical machine learning ...
Over the past year I’ve reviewed half a dozen open source machine learning and/or deep learning frameworks: Caffe, Microsoft Cognitive Toolkit (aka CNTK 2), MXNet, Scikit-learn, Spark MLlib, and ...
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