Plan your projects and define important tasks and actions

Get Started. It's Free
or sign up with your email address
iLab1 by Mind Map: iLab1

1. Stakeholders

1.1. Professor Kailash Awati

1.1.1. Mentor

1.2. Inventor of Ailira

1.3. Adrian

1.3.1. Client

2. Resources

2.1. Learning

2.1.1. Python Datacamp // Access was interrupted 2 days ago Coursera Introduction to Data Science in Python University of Michigan

2.1.2. Deep Learning Machine Learning by Stanford University Deep Learning for Natural Language Processing (Stanford University)

2.2. Human

3. Scope

3.1. What is included

3.1.1. Clustering similarities in law

3.1.2. Deliver the clustering in a manner that can be used to train the chatbot tool.

3.2. What is excluded

3.2.1. Improvements or implementations on the chatbot tool.

4. Milestones

4.1. Assignment 1 Part A

4.1.1. Due 6PM, Friday, 18 August

4.1.2. Deliverable Design journal in CICAround blog Learning Goals and Weekly entries

4.2. Assignment 1 Part B

4.2.1. Due 9AM, Friday, 25 September

4.2.2. Deliverable Design journal in CICAround blog Interim Status Report

4.3. Assignment 1 Part C

4.3.1. Due 9AM, Monday, 23 October

4.3.2. Deliverable Project Design Journal All components submitted via UTSOnline

4.4. Assignment 2

4.4.1. Due 6PM, Thursday, 12 October

4.4.2. Deliverable Project Showcase present the outcomes of their work on the data challenge they have undertaken on behalf of their chosen client

4.5. Assignment 3

4.5.1. Desc Professional Showcase

4.5.2. Due 9AM, Monday, 6 November

5. Constraints

5.1. Deadline

5.1.1. 9AM, Monday, 6 November

5.2. Requirements

5.2.1. Legal

5.3. Technical

5.3.1. Can the cloud (AWS) be used?

5.3.2. Which dataset will I have access to?

6. Overview

6.1. Motivation

6.1.1. Law is derived from unstructured data that is often similar in concept, but different in presentation. In this way, the client (Cartland Law) aims at taking a large body of legal documents and cluster similarities in them to create a trained tool that can understand the law in more detail than the tool they currently have. Cartland's tool that understands the law is a chatbot called Ailira, which was able to pass a universty tax law exam.

6.1.2. links Ailira - Legal Artificial Intelligence Artificial Intelligence Ailira's University Tax Law Exam Ailira | Cartland Law

6.2. Goals

6.2.1. Client Cluster similarities in law to help Cartland Law building their tool. Further details shall be elicited with client

6.2.2. Learning Programming and scripting languages Achieve the Advanced level in Python programming language, specially in Deep Learning Techniques on Natural Language Processing Analytics, predictive modelling and machine learning Achieve the Advanced level, specially in Deep Learning models (Neural Networks and Convolutional Neural Networks) Communication Achieve the Competent level Computing systems, platforms, security, integration Learn how to set and use cloud based High Performance Computing

7. Deliverables

7.1. UTS

7.1.1. Design Journal Where CICAround blog Content 1: Project Goals 2: 3: Interim project status report 4: Professional development outcomes Record discoveries, milestones and challenges Assessment Criteria Pre-defined Own

7.1.2. Project Showcase Goal Present a multimodal narrative summarisation of the knowledge gained from their data investigations throughout the semester so that they can deliver advice in story form to their client Criteria Client briefing/presentation Supporting documentation A detailed Assessment Brief outlining specific requirements for each assessment task will be available in UTSOnline. Ensure you consult these briefs before you undertake the assessment tasks.