deep learning Archives - Petamind https://petaminds.com/tag/deep-learning/ A.I, Data and Software Engineering Tue, 05 Oct 2021 06:08:04 +0000 en-US hourly 1 https://wordpress.org/?v=6.9.4 https://petaminds.com/wp-content/uploads/2019/09/ic_launcher.png deep learning Archives - Petamind https://petaminds.com/tag/deep-learning/ 32 32 Continue training big models on less powerful devices https://petaminds.com/continue-training-big-models-on-less-powerful-devices/ https://petaminds.com/continue-training-big-models-on-less-powerful-devices/#respond Sun, 22 Mar 2020 00:51:57 +0000 https://petaminds.com/?p=2338 It would not be a surprise that you may not have a powerful expensive machine to train a complicate model. You may experience the problem of not enough memory during training in some epoch. This article demonstrates a simple workaround for this. The problem Training deep learning models requires a lot of computing power. For […]

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]]> https://petaminds.com/continue-training-big-models-on-less-powerful-devices/feed/ 0 Create bipartite graph from a rating matrix https://petaminds.com/create-bipartite-graph-from-a-rating-matrix/ https://petaminds.com/create-bipartite-graph-from-a-rating-matrix/#respond Sun, 15 Mar 2020 01:41:19 +0000 https://petaminds.com/?p=2305 As deep learning on graphs is trending recently, this article will quickly demonstrate how to use networkx to turn rating matrices, such as MovieLens dataset, into graph data. The rating data We use rating data from the movie lens. The rating data is loaded into rdata which is a Pandas DataFrame. This article demonstrates how […]

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]]> https://petaminds.com/create-bipartite-graph-from-a-rating-matrix/feed/ 0 A.I in agriculture – Fruit Grading with Keras (part 2) https://petaminds.com/a-i-in-agriculture-fruit-grading-with-keras-part-2/ https://petaminds.com/a-i-in-agriculture-fruit-grading-with-keras-part-2/#respond Sun, 06 Oct 2019 07:05:15 +0000 https://petaminds.com/?p=994 In part 1, we introduced fruit classification with pure python implementation. In this part, we will use the Keras library instead. What is Keras Keras is an open-sourceneural-network library written in Python. It is capable of running on top of TensorFlow, Microsoft Cognitive Toolkit, Theano, or PlaidML. Designed to enable fast experimentation with deep neural networks, it focuses on being user-friendly, modular, and extensible.  […]

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]]> https://petaminds.com/a-i-in-agriculture-fruit-grading-with-keras-part-2/feed/ 0 AI in agriculture: fruit grading (Part 1) https://petaminds.com/use-ai-technology-in-agriculture-for-fruit-grading-part-1/ https://petaminds.com/use-ai-technology-in-agriculture-for-fruit-grading-part-1/#comments Thu, 26 Sep 2019 03:37:27 +0000 http://petaminds.com/?p=645 During a meet up last month, a friend told me about the current project on a farm in New Zealand. They want to build a system to grade their fruits and AI is the technology they are looking for. It inspired me to write about how machine learning can help in solving such a problem. […]

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]]> https://petaminds.com/use-ai-technology-in-agriculture-for-fruit-grading-part-1/feed/ 1 An example to Graph Convolutional Network https://petaminds.com/an-example-to-graph-convolutional-network/ https://petaminds.com/an-example-to-graph-convolutional-network/#respond Mon, 23 Sep 2019 02:03:09 +0000 http://petaminds.com/?p=633 In my research, there are many problems involve networks of different types, e.g. social network, online-trading networks, crowd-sourcing, etc. I was so happy to find a new powerful tool for my research, the graph convolutional network, which applies deep learning on graph structures. Graph convolutional network (GCN) There is currently no official definition for GCN. […]

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]]> https://petaminds.com/an-example-to-graph-convolutional-network/feed/ 0 Make use of GG Colab and Jupyter notebook https://petaminds.com/make-use-of-gg-colab-and-jupyter-notebook/ https://petaminds.com/make-use-of-gg-colab-and-jupyter-notebook/#comments Mon, 16 Sep 2019 03:00:15 +0000 http://petaminds.com/?p=561 I decided to share this topic while doing research on Deep Learning on Graph, the latest trend in Deep learning. One of the challenges that I had was to the processing power of my laptop while processing hundreds of thousands of nodes. While buying a new laptop with a good GPU is not cheap, around […]

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