More importantly, it lets AI researchers undertake entirely new types of work, not possible using current technologies, to drive the next great breakthroughs in general Machine Intelligence.

More Uses of the Machine Intelligence Toolkit:


• Lead cutting edge research in Machine Intelligence andMachine Learningapplications.
  
  

• Help you construct the future of Machine Intelligence.
  
  


Coordinate Machine Intelligence: customer facing and focused on key strategic hospitality customers.

More Uses of the Machine Intelligence Toolkit:


• Lead cutting edge research in Machine Intelligence and Machine Learning applications.
  
  

• Initiate Machine Intelligence: design, develop, implement and maintain analytical models and solutions using optimization, simulation, Machine Learning and other advancedAnalytical Capabilitiesto support Supply Chain objectives.
  
  

• Guide Machine Intelligence:Enterprise ProductappliedResearch Teamis composed of applied quantitative and computational experts using Machine Learning, statistics and Operations Research to bring in step level improvements in efficiency and scalability across the entire suite of enterprise products.
  
  

• Identify/develop appropriate Machine Learning/Deep Learning/Data Mining/Text Mining techniques to uncover the value of the data.
  
  

• Develop innovative methods in Machine Learning and Data Analytics for Cyber andInsider Threatdetection in corporate andCustomer Environments
  
  

• Solidify expertise in bayesian optimization, probabilistic Machine Learning, Knowledge Graphs,Recommendation Systems or Deep Learning.
  
  

• Steer Machine Intelligence: research, experiment, and evaluate statistical and Machine Learning techniques to develop Fraud Detection systems that satisfy Business Requirements and Security Policies.
  
  

• Coordinate Machine Intelligence: execution of Machine Learning projects to address specific business problems determined by consultation withBusiness Partners
  
  

• Develop Machine Learning and Deep Learning algorithms.
  
  

• Audit Machine Intelligence: development of statistical models and Machine Learning framework for evaluation of execution methods and algorithms.
  
  

• Provide engineering and technical leadership for Project Planning and implementation activities with internal and external teams as it relates to analytics, platform integration,Digital Ecosystem AI and Machine Learning.
  
  

• Identify Machine Intelligence: Machine Learning, Statistical Modeling, Data Mining, Natural Language Processing to improve Data Collection and Data Quality of datasets maintained by your organization.
  
  

• Take a Machine Learning project from conception to reality, creating an API Endpoint serving a predictive model that could be used live on your website or for internal efficiencies.
  
  

• Confirm your business makes machine Software Updates to fix bugs in the initial installation and introduces extensions to current systems to add additional functionality or boost performance.
  
  

• Implement business and ITData Requirementsthrough new Data Strategies and designs across allData Platforms(relational, dimensional, and NoSQL) and data tools (reporting, visualization, analytics, and Machine Learning).
  
  

• Apply advanced Statistical Modeling and Machine Learning algorithms to solve complex problems and improvE Business strategy and decisions directly.
  
  

• Govern Machine Intelligence: algorithm development in areas as pattern or gesture recognition, adaptive filters, Machine Learning, sensor / Image Processing, or controls.
  
  

• Head Machine Intelligence: design and build scalable, efficient and automated processes for large scale Data Analysis, Machine LearningModel Development model validation and servings.
  
  

• Lead cutting edge research using tools as Machine Learning, Natural Language Processing, Robotic Process Automation and Blockchain amongst other capabilities.
  
  

• Pilot Machine Intelligence: research, experiment, and evaluate statistical and Machine Learning techniques to develop Fraud Detection systems that satisfy Business Requirements and Security Policies.
  
  

• Develop Machine Intelligence: algorithmic design and Machine Learning techniques for efficient and scalable solving of computational complex calculation, Data Processing, andAutomated Reasoningtasks.
  
  

• Evaluate Machine Intelligence: Software Development.perience with scripting languages andSoftware Platformsrelated to advanced statistics, optimization, Data Mining and/or Machine Learning and visualization.
  
  

• Initiate Machine Intelligence: development of 2d general arrangement drawing of machine and peripheral equipment layout specific to customer and project requirements using Autodesk AutoCAD software.
  
  

• Pilot Machine Intelligence: Artificial intelligence, Machine Learning, Chatbots, linguistics, Metadata, structured content.
  
  

• Analyze large sets of collected server telemetry data, create Machine Learning models to predict expected performance.
  
  

• Develop Machine Learning graph compiler.
  
  

• Supervise Machine Intelligence: act as a resource to the Machine Learning team with regards to Data Lifecycle management.
  
  

• Coordinate Machine Intelligence: research, experiment, and evaluate statistical and Machine Learning techniques to develop Fraud Detection systems that satisfy Business Requirements and Security Policies.
  
  

• Ensure you motivate; lead the use of Statistical Analysis and Machine Learning techniques towards building intelligent and/or Predictive Analytics solutions.
  
  

• Control Machine Intelligence: regression models, causal inference in marketing andProduct Launches advanced bayesian techniques and Machine Learning modeling techniques.
  
  

• Standardize Machine Intelligence: Artificial intelligence and Machine Learning to design, prototype, and build solutions to business problems.
  
  

• Direct Machine Intelligence: Conflict Management can find common ground and get cooperation with little noise, handles tough agreements and settles disputes equitably.
  
  


Save time, empower your teams and effectively upgrade your processes with access to this practical Machine Intelligence Toolkit and guide. Address common challenges with best-practice templates, step-by-step Work Plans and maturity diagnostics for any Machine Intelligence related project.

Download the Toolkit and in Three Steps you will be guided from idea to implementation results.

The Toolkit contains the following practical and powerful enablers with new and updated Machine Intelligence specific requirements:

STEP 1: Get your bearings

Start with...


• The latest quick edition of the Machine Intelligence Self Assessment book in PDF containing 49 requirements to perform a quickscan, get an overview and share with stakeholders.


Organized in a Data Driven improvement cycle RDMAICS (Recognize, Define, Measure, Analyze, Improve, Control and Sustain), check the…


• Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation


Then find your goals...

STEP 2: Set concrete goals, tasks, dates and numbers you can track

Featuring 999 new and updated case-based questions, organized into seven core areas of Process Design, this Self-Assessment will help you identify areas in which Machine Intelligence improvements can be made.

Examples; 10 of the 999 standard requirements:


1. What are current Machine Intelligence paradigms?
   
   

2. What resources are required for the improvement efforts?
   
   

3. What data is gathered?
   
   

4. How is Knowledge Sharing about Risk Management improved?
   
   

5. Who else should you help?
   
   

6. How do you govern and fulfill your societal responsibilities?
   
   

7. Is the Quality Assurance team identified?
   
   

8. Are you able to realize any cost savings?
   
   

9. What are the Machine Intelligence investment costs?
   
   

10. Is the measure of success for Machine Intelligence understandable to a variety of people?
    
    


Complete the self assessment, on your own or with a team in a workshop setting. Use the workbook together with the self assessment requirements spreadsheet:


• The workbook is the latest in-depth complete edition of the Machine Intelligence book in PDF containing 994 requirements, which criteria correspond to the criteria in...


Your Machine Intelligence self-assessment dashboard which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next:


• The Self-Assessment Excel Dashboard; with the Machine Intelligence Self-Assessment and Scorecard you will develop a clear picture of which Machine Intelligence areas need attention, which requirements you should focus on and who will be responsible for them:
  
  


• Shows your organization instant insight in areas for improvement: Auto generates reports, radar chart for maturity assessment, insights per process and participant and bespoke, ready to use, RACI Matrix

• Gives you a professional Dashboard to guide and perform a thorough Machine Intelligence Self-Assessment

• Is secure: Ensures offline Data Protection of your Self-Assessment results

• Dynamically prioritized projects-ready RACI Matrix shows your organization exactly what to do next:



STEP 3: Implement, Track, follow up and revise strategy

The outcomes of STEP 2, the self assessment, are the inputs for STEP 3; Start and manage Machine Intelligence projects with the 62 implementation resources:


• 62 step-by-step Machine Intelligence Project Management Form Templates covering over 1500 Machine Intelligence project requirements and success criteria:


Examples; 10 of the check box criteria:


1. Cost Management Plan: Eac -estimate at completion, what is the total job expected to cost?
   
   

2. Activity Cost Estimates: In which phase of the Acquisition Process cycle does source qualifications reside?
   
   

3. Project Scope Statement: Will all Machine Intelligence project issues be unconditionally tracked through the Issue Resolution process?
   
   

4. Closing Process Group: Did the Machine Intelligence Project Team have enough people to execute the Machine Intelligence project plan?
   
   

5. Source Selection Criteria: What are the guidelines regarding award without considerations?
   
   

6. Scope Management Plan: Are Corrective Actions taken when actual results are substantially different from detailed Machine IntelligenceProject Plan(variances)?
   
   

7. Initiating Process Group: During which stage of Risk planning are risks prioritized based on probability and impact?
   
   

8. Cost Management Plan: Is your organization certified as a supplier, wholesaler, regular dealer, or manufacturer of corresponding products/supplies?
   
   

9. Procurement Audit: Was a formal review of tenders received undertaken?
   
   

10. Activity Cost Estimates: What procedures are put in place regarding bidding and cost comparisons, if any?


 
Step-by-step and complete Machine Intelligence Project Management Forms and Templates including check box criteria and templates.

1.0 Initiating Process Group:


• 1.1 Machine Intelligence project Charter

• 1.2 Stakeholder Register

• 1.3 Stakeholder Analysis Matrix


2.0 Planning Process Group:


• 2.1 Machine Intelligence Project Management Plan

• 2.2 Scope Management Plan

• 2.3 Requirements Management Plan

• 2.4 Requirements Documentation

• 2.5 Requirements Traceability Matrix

• 2.6 Machine IntelligenceProject ScopeStatement

• 2.7 Assumption and Constraint Log

• 2.8 Work Breakdown Structure

• 2.9 WBS Dictionary

• 2.10 Schedule Management Plan

• 2.11 Activity List

• 2.12 Activity Attributes

• 2.13 Milestone List

• 2.14 Network Diagram

• 2.15 Activity Resource Requirements

• 2.16 Resource Breakdown Structure

• 2.17 Activity Duration Estimates

• 2.18 Duration Estimating Worksheet

• 2.19 Machine Intelligence project Schedule

• 2.20 Cost Management Plan

• 2.21 Activity Cost Estimates

• 2.22 Cost Estimating Worksheet

• 2.23 Cost Baseline

• 2.24 Quality Management Plan

• 2.25 Quality Metrics

• 2.26 Process Improvement Plan

• 2.27 Responsibility Assignment Matrix

• 2.28 Roles and Responsibilities

• 2.29 Human Resource Management Plan

• 2.30Communications ManagementPlan

• 2.31 Risk Management Plan

• 2.32 Risk Register

• 2.33 Probability and Impact Assessment

• 2.34 Probability and Impact Matrix

• 2.35 Risk Data Sheet

• 2.36 Procurement Management Plan

• 2.37 Source Selection Criteria

• 2.38 Stakeholder Management Plan

• 2.39 Change Management Plan


3.0 Executing Process Group:


• 3.1 Team Member Status Report

• 3.2 Change Request

• 3.3 Change Log

• 3.4 Decision Log

• 3.5 Quality Audit

• 3.6 Team Directory

• 3.7 Team Operating Agreement

• 3.8Team PerformanceAssessment

• 3.9 Team Member Performance Assessment

• 3.10 Issue Log


4.0 Monitoring and Controlling Process Group:


• 4.1 Machine Intelligence project Performance Report

• 4.2 Variance Analysis

• 4.3 Earned Value Status

• 4.4 Risk Audit

• 4.5 Contractor Status Report

• 4.6 Formal Acceptance


5.0 Closing Process Group:


• 5.1 Procurement Audit

• 5.2 Contract Close-Out

• 5.3 Machine Intelligence project or Phase Close-Out

• 5.4 Lessons Learned


Results

With this Three Step process you will have all the tools you need for any Machine Intelligence project with this in-depth Machine Intelligence Toolkit.

In using the Toolkit you will be better able to:


• Diagnose Machine Intelligence projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices

• Implement evidence-based Best Practice strategies aligned with overall goals

• Integrate recent advances in Machine Intelligence and put Process Design strategies into practice according to Best Practice guidelines


Defining, designing, creating, and implementing a process to solve a business challenge or meet a business objective is the most valuable role; In EVERY company, organization and department.

Unless you are talking a one-time, single-use project within a business, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?'

This Toolkit empowers people to do just that - whether their title is entrepreneur, manager, consultant, (Vice-)President, CxO etc... - they are the people who rule the future. They are the person who asks the right questions to make Machine Intelligence investments work better.

This Machine Intelligence All-Inclusive Toolkit enables You to be that person.

Includes lifetime updates

Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.