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5 Step Guide to Scalable Deep Learning Pipelines with d6tflow
How to turn a typical pytorch script into a scalable d6tflow DAG for faster research & development.
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Version Control for Data Science: Tracking Machine Learning Models and Datasets
I am a Git god, why do I need another version control system for Machine Learning Projects?
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Ensemble Methods for Machine Learning: AdaBoost
It turned out that, if we ask the weak algorithm to create a whole bunch of classifiers (all weak for definition), and then combine them all, what may figure out is a stronger classifier.
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 Train sklearn 100x Faster
As compute gets cheaper and time to market for machine learning solutions becomes more critical, we’ve explored options for speeding up model training. One of those solutions is to combine elements from Spark and scikit-learn into our own hybrid solution.
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Common Machine Learning Obstacles
In this blog, Seth DeLand of MathWorks discusses two of the most common obstacles relate to choosing the right classification model and eliminating data overfitting.
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 I wasn’t getting hired as a Data Scientist. So I sought data on who is.
Instead of focusing on skills thought to be required of data scientists, we can look at what they have actually done before.
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TensorFlow Optimization Showdown: ActiveState vs. Anaconda
In this TensorFlow tutorial, you’ll learn the impact of optimizing both operators and entire graphs, how to efficiently organize data in training and testing datasets to minimize data shuffling, and how to identify a well-optimized model using Anaconda and ActivePython.
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Advice on building a machine learning career and reading research papers by Prof. Andrew Ng
This blog summarizes the career advice/reading research papers lecture in the CS230 Deep learning course by Stanford University on YouTube, and includes advice from Andrew Ng on how to read research papers.
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Python Libraries for Interpretable Machine Learning
In the following post, I am going to give a brief guide to four of the most established packages for interpreting and explaining machine learning models.
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Top 10 Data Science Use Cases in Energy and Utilities
In this article, we will consider the most vivid data science use cases in the industry of energy and utilities.
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Train sklearn 100x Faster
I wasn’t getting hired as a Data Scientist. So I sought data on who is.
Advice on building a machine learning career and reading research papers by Prof. Andrew Ng