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• ML curriculum
  ....com/ZuzooVn/machine-learning-for-software-engineers/blob/master/README.md ML for Software Engineers] also looks wonderful * [http://www.holehouse.org/mlclass/ Andrew Ng's Stanford ML course, unofficial notes] as Ersatz for the Coursera video-course.
  3 KB (278 words) - 14:47, 16 May 2018

Page text matches

• A quick complete tutorial to save and restore Tensorflow models – CV-Tricks.com
  k=tf, tensorflow, ml, nn [[Category: ML]]
  255 bytes (27 words) - 12:00, 7 August 2018
• ODDS – Outlier Detection DataSets
  k=datasets, data, outliers, outlier detection, anomaly detection, ml, machine learning, nn [[Category: ML]]
  216 bytes (27 words) - 08:04, 7 August 2018
• PrithivirajDamodaran/Styleformer: A Neural Language Style Transfer framework
  k=NLP, ML, github, style [[Category: ML]]
  201 bytes (24 words) - 14:15, 2 August 2021
• Fast and Accurate Document Detection for Scanning - Dropbox
  k=vision, hough lines, document detection, ml, dropbox, opencv [[Category: ML]]
  261 bytes (28 words) - 10:29, 28 January 2021
• A Complete 4-Year Course Plan for an Artificial Intelligence Undergraduate Degree - Mihail Eric
  k=ml, ai, machine learning, bachelor, curriculum [[Category: ML]]
  379 bytes (42 words) - 14:20, 1 June 2020
• (1809.08799) Chargrid: Towards Understanding 2D Documents
  k=papers, nlp, ml, vision, to read [[Category: ML]]
  215 bytes (25 words) - 07:12, 19 January 2021
• The Curse of Dimensionality in Classification
  k=ml, computer vision, machine learning, dimensionality, classification, visuali [[Category: ML]]
  305 bytes (32 words) - 16:33, 4 May 2018
• Distill — Latest articles about machine learning
  k=ml, visualization, explorables [[Category: ML]]
  248 bytes (30 words) - 19:53, 16 May 2018
• Machine Learning Basics — Part 4 — Anomaly Detection, Recommender Systems and Scaling
  k=ml, machine learning, anomaly detection, anomaly, outliers, nn [[Category: ML]]
  331 bytes (31 words) - 06:56, 8 August 2018
• Yes you should understand backprop – Andrej Karpathy – Medium
  k=ml, todo, machine learning, backprop, back-propagation, backpropagation, to re [[Category: ML]]
  299 bytes (34 words) - 10:39, 18 January 2019
• List of Public Data Sources Fit for Machine Learning - The Official Blog of BigML.com
  k=ml, data sources, machine learning, data [[Category: ML]]
  257 bytes (33 words) - 08:01, 7 August 2018
• Unsupervised learning of artistic styles with archetypal style analysis - the morning paper
  k=to read, ml, analysis, classification, machine learning, art, style [[Category: ML]]
  359 bytes (37 words) - 17:36, 12 January 2019
• Layout-parser/modelzoo.md at master · Layout-Parser/layout-parser
  k=layout parsing, ml, github, vision, work [[Category: ML projects]]
  272 bytes (33 words) - 10:28, 28 January 2021
• All Posts - Holehouse.org
  k=to read, python, programming, data science, ml, machine learning, site, blog, posts [[Category: ML]]
  277 bytes (37 words) - 14:49, 18 April 2018
• Hollywood Superstitions vs. Data Science: Investigating for 99PI • Andrew and Zachary Burchill
  k=movies, ml, nlp, experiment, superstition, ds, applied ml, hollywood [[Category: ML]]
  573 bytes (75 words) - 17:18, 7 April 2020
• Jonathan Hui blog
  |Jonathan Hui blog - Blog about ML and Tensorflow k=to read, ml, tf, tensorflow, machine learning
  253 bytes (38 words) - 20:36, 25 March 2020
• How to Use t-SNE Effectively
  k=to read, t-sne, dimensionality, ml, data, machine learning, data analysis, data science [[Category: ML]]
  248 bytes (32 words) - 19:13, 25 January 2019
• My receipts (pdf scans) - Kaggle
  k=datasets, ml
  147 bytes (20 words) - 11:48, 15 June 2021
• Surprising shared word etymologies - Daniel de Haas
  k=etymology, language, embeddings, nlp, ml, words
  261 bytes (30 words) - 10:36, 14 June 2021
• Overfitting - Wikipedia
  k=statistics, machine learning, ml, data analysis
  230 bytes (32 words) - 16:41, 22 January 2017

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