[singa] branch dev-postgresql updated: readme for malaria prediction with cnn model

[zh...@apache.org]

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The following commit(s) were added to refs/heads/dev-postgresql by this push:
     new df937b01 readme for malaria prediction with cnn model
     new 8aca66c5 Merge pull request #1060 from liuchangshiye/malaria-cnn
df937b01 is described below

commit df937b01223ad17138504ba4a381df494e547309
Author: liuchangshiye <li...@gmail.com>
AuthorDate: Tue May 30 20:22:52 2023 +0800

    readme for malaria prediction with cnn model
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 examples/malaria_cnn/README.md | 44 ++++++++++++++++++++++++++++++++++++++++++
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+<!--
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+    regarding copyright ownership.  The ASF licenses this file
+    to you under the Apache License, Version 2.0 (the
+    "License"); you may not use this file except in compliance
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+
+      http://www.apache.org/licenses/LICENSE-2.0
+
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+    KIND, either express or implied.  See the License for the
+    specific language governing permissions and limitations
+    under the License.
+-->
+
+# Singa for Malaria Detection Task
+
+## Malaria
+
+Malaria is caused by parasites and could be transmitted through infected mosquitoes. There are about 200 million cases worldwide, and about 400,000 deaths per year, therefore, malaria does lots of harm to global health.
+
+Although Malaria is a curable disease, inadequate diagnostics make it harder to reduce mortality, as a result, a fast and reliable diagnostic test is a promising and effective way to fight malaria.
+
+To mitigate the problem, we use Singa to implement a machine learning model to help with Malaria diagnosis. The dataset is from Kaggle https://www.kaggle.com/datasets/miracle9to9/files1?resource=download. Please download the dataset before running the scripts.
+
+## Structure
+
+* `data` includes the scripts for preprocessing Malaria image datasets.
+
+* `model` includes the CNN model construction codes by creating
+  a subclass of `Module` to wrap the neural network operations 
+  of each model.
+
+* `train_cnn.py` is the training script, which controls the training flow by
+  doing BackPropagation and SGD update.
+
+## Command
+```bash
+python train_cnn.py cnn malaria -dir pathToDataset
+```
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