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When Machines Learn
Sharing industry research to advance data science and machine learning for industrial processes.
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How I landed my data scientist position at Tagup
How I landed my data scientist position at Tagup
Mastering technical interviews with autoencoders and visualizations
Lorenzo Bucci
Apr 12, 2022
Methods for Imputation with Hidden Markov Models
Methods for Imputation with Hidden Markov Models
Using inference to fill in missing values in sequential data
Anna Haensch
Oct 30, 2020
A Guide to Distributed Tensorflow: Part 2
A Guide to Distributed Tensorflow: Part 2
How to set up large scale, distributed training of TensorFlow models using Kubeflow.
Roshan Thaikkat
Oct 16, 2020
Dask Performance Boosts for Model Training
Dask Performance Boosts for Model Training
Tips and Tricks to speed up distributed training when using Dask
Daniel Hathcock
Oct 13, 2020
A Guide to Distributed Tensorflow: Part 1
A Guide to Distributed Tensorflow: Part 1
How to set up efficient input data pipelines for deep learning using TFRecord and tf.data.Dataset API
Roshan Thaikkat
Oct 9, 2020
How to use data visualization to validate imputation tasks
How to use data visualization to validate imputation tasks
Creating custom charts can help us better understand, validate, and improve imputation tasks in data science and machine learning.
Ben Dexter Cooley
Oct 2, 2020
Imputation and its Applications
Imputation and its Applications
Using imputation for model validation, data preprocessing and generative modeling.
Anna Haensch
Sep 25, 2020
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