Ai finds treasure Philippines – #disney #ai #treasure #adventure #philippines #trends #animation

Ai finds treasure Philippines – #disney #ai #treasure #adventure #philippines #trends #animation

HomeA-Z of Stories about AI (Azai)Ai finds treasure Philippines – #disney #ai #treasure #adventure #philippines #trends #animation
Ai finds treasure Philippines – #disney #ai #treasure #adventure #philippines #trends #animation
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The Philippines has a rich history and is often associated with legends about hidden treasures and treasure maps. One of the most famous stories is that of the Yamashita Treasure, also known as the Golden Lily Treasure. This alleged treasure is said to have been collected by the Japanese during World War II and hidden in various locations in the Philippines.

In the Philippines, treasure hunting activities are regulated, and individuals or groups interested in conducting excavations must obtain necessary permits from the National Museum and other relevant authorities to ensure the protection of cultural heritage and artifacts.

Artificial intelligence can play a role in certain aspects of determining the authenticity of documents, artifacts or historical records, including treasure maps.

AI technologies, such as image analysis and pattern recognition, can be used to examine the physical characteristics of documents or maps. For example, digital forensic investigation and analysis tools can help detect signs of forgery or tampering in images or documents.

Here are some resources to help you get started building a neural network:

1. **freecodecamp.org** has a detailed tutorial on how to build a neural network from scratch with Python and numpy. The tutorial covers the basics of neural networks, the mathematical functions that generate nonlinear output from linear input, and how to train them on any data set using gradient descent. https://www.freecodecamp.org/news/building-a-neural-network-from-scratch/

2. **Neural Designer** provides a step-by-step guide to building a neural network that approximates a function defined by a set of data points. The tutorial covers creating an approximation model, configuring the dataset, setting up the network architecture, and training the neural network. https://www.neuraldesigner.com/learning/user-guide/design-a-neural-network/

3. **Machine Learning Mastery** includes a tutorial on how to develop your first neural network with PyTorch. The tutorial covers loading data, defining the PyTorch model, defining the loss function and optimizers, running a training loop, evaluating the model, and making predictions. https://machinelearningmastery.com/develop-your-first-neural-network-with-pytorch-step-by-step/

4. **RStudio** has a two-part series on building a neural net from scratch using R. The tutorial covers building a neural net that contains a single hidden layer and performs binary classification using a vectorized implementation of backpropagation, all written in basic R. https://rviews.rstudio.com/2020/07/20/shallow-neural-net-from-scratch-using-r-part-1/

5. **PyTorch Tutorials** provides a beginner's guide to building a neural network. The tutorial covers obtaining a device for training, defining the class, model layers, and more. https://pytorch.org/tutorials/beginner/basics/buildmodel_tutorial.html

1. **Historical documents and archives:**
– Source: National archives, historical databases, government archives.

2. **Yamashita's moves:**
– Source: military documents, war diaries, historical accounts.

3. **Tunnel locations:**
– Source: Historical documents, local accounts, government documents.

4. **Ship manifests and routes:**
– Source: Maritime archives, ship logbooks, historical data.

5. **Geospatial data:**
– Source: Geographic Information System (GIS) databases, topographic maps.

6. **Temporary data:**
– Source: historical timelines, war diaries, event reports.

7. **Keywords for pattern recognition:**
– Source: text mining algorithms, historical lexicons.

8. **Network Analytics Data:**
– Source: Biographical data, historical data, social connections.

9. **Predictive Modeling Data:**
– Source: historical patterns, location data, event timelines.

10. **Resources for cross-validation:**
– Source: independent historical accounts, academic research, multiple archives.

Countries that claim the Japanese stole their gold

1. **Philippines:**
– Significant claims regarding the Yamashita Treasure and looting during the Japanese occupation.

2. **China:**
– Allegations of widespread looting by Japanese forces during their occupation of China.

3. **Korea:**
– Reports of looting and seizure of valuables during the Japanese occupation of Korea.

4. **Malaysia and Singapore:**
– Claims of plunder and seizure of property by Japanese forces during the occupation of Malaya and Singapore.

5. **Indonesia:**
– Accusations of plunder and seizure of valuable resources during the Japanese occupation of Indonesia.

6. **Burma (Myanmar):**
– Reports of looting and pillaging by Japanese forces during their occupation of Burma.

7. **Thailand:**
– Claims of plunder and seizure of property during the Japanese occupation of Thailand.

8. **Netherlands:**
– Accusations of plundering Dutch colonial possessions during the Japanese occupation of the Dutch East Indies (Indonesia).

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