Learning DeadCL DeadCL Tutorials DeadCL Syntax DeadCL MBS

Walk throughs

Author Keys Conversations Libraries Arrays

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Learning DeadCL

DeadLetter is an open machine learning platform for research, personal and commercial applications.

Here you'll find all the information relevant to understand and deploy a Dead Conversation.
Using either our "drop" & "retrieve" method or PARCEL our programable interface (API).

The Basics

Here we'll guide you through the basics of DeadLetter

- Understanding DeadCL
- Inputs & Outputs
- DeadCL Syntax
- DeadCL MBS  (Meaning Based Syntax)
- DeadLetter Terminology
- Deploying DeadLetter

The Components

DeadCL is comprised of the following components;

- Author Key
- DeadLetter Libraries
- DeadLetter Conversations
- DeadLetter Arrays

Writing Conversations

Applications on DeadLetter are called Conversations, here we'll discuss how you write one

- Setting Authorship
- Structuring & Building Flow
- Conversation inputs & outputs
- Changing Default URL(s)


Once you understand a handful of basic principles writing, maintaining & interpreting Conversations is second Nature.

- Detecting an object
- Substituting an object
- Pulling input(s) & Link(s)
- Posting output(s)
- Output addresses

Drop & Retrieve Method (DRM)

By default deadCL is configured to simply read from
a remote URI & post to a 'local' URI.

- DRM Overview
- What is 'dropping'
- What is 'retrieving'

Parcel V4

Parcel introduces the basic functions of an API - that remains entirely Author programable.

- DeadLetter Parcel basics
- Configurable Helper for Author Drops (CHAD)
- Parcel for messaging (Arnold)
- Parcel for Conversation inputs & outputs


To test your knowledge of DeadCL we've created the following tutorials;

Kinesthetic Tutorials
- Hangman (Understanding Linear Graphics)
- Parcel Chatbot (using Arnold)
- Database creation & management using Parcel
- deadCL chat-bot using emails (using CHAD)
- Object Recognition (coming soon)
- Basic Person Detection (coming soon)
- Basic Text Encryption (coming soon)