Showing posts with label AI. Show all posts
Showing posts with label AI. Show all posts

Tuesday, September 02, 2025

GenAi resources

 Here are some GenAi resources:


Image Generators



See also this post:





Tuesday, March 09, 2021

Machine Learning and AI for You to Learn

 

Image by Gerd Altmann from Pixabay

I am going a webinar/presentation titled "5 Steps to Play With and Learn AI" On March 23, 2021.  The live webinar is free (you can register here) and will be available soon afterward on-demand with other of my webinars.

This is reference information for that presentation.

 The 5 steps to learning:

  1. Awareness / Decision / Goal
  2. Play / Experience / Experiment
  3. Learn
  4. Apply
  5. Share

1. Awareness: 

The fact that you are here shows that you are aware. Now, you need to decide if you want to pursue it. Then, set a goal.

Forbes "Top 10 Tech Job Skills Predicted To Grow The Fastest In 2021" names AI as a top paying job.

Coursera story: "How Stijn landed his new job after completing the IBM Applied AI Professional Certificate"

Data Science compared to Machine Learning "When Data Science Met Machine Learning" (this includes the Five Vs of data: volume, variety, veracity, value and velocity

Towards Data Science: "Data Science vs. Artificial Intelligence vs. Machine Learning vs. Deep Learning" by Sunny Srinidhi.

UpGrad: "Data Science vs AI: Difference Between Data Science and Artificial Intelligence" by Rohit Sharma Dec 17, 2019

SimpliLearn "AI vs Data Science: Mapping Your Career Path" By Ronald Van Loon Last updated on Feb 5, 2021

Thinkful: "Data Science vs Artificial Intelligence" includes salary information and career track information

New Jersey Institute of Technology: One of the only B.S. degrees in Data Science in the Nation

2. Play and Experiment

Google

https://experiments.withgoogle.com/

https://experiments.withgoogle.com/collection/ai 

Includes: AI and Writing, AI and Learning, AI and Drawing, AI and Music

Google Vision AI

Microsoft

https://www.microsoft.com/en-us/research/group/deep-learning-group/

https://lionbridge.ai/articles/10-craziest-ai-experiments-to-try-online-today/

IBM:

https://www.ibm.org/activities/

TJ BOT: https://www.ibm.org/activities/tjbot

Virtual TJ BOT: https://www.ibm.org/activities/virtual-tjbot

Machine Learning for Kids: https://www.ibm.org/activities/machine-learning-for-kids  

Watson Conversation: https://www.ibm.org/activities/watson-conversation

https://www.research.ibm.com/artificial-intelligence/experiments/learn-and-play/

GAN

This x does not exist

https://thisxdoesnotexist.com/

https://machinelearningmastery.com/impressive-applications-of-generative-adversarial-networks/

https://poloclub.github.io/ganlab/

https://www.producthunt.com/alternatives/this-x-does-not-exist

Generative Engine: https://experiments.runwayml.com/generative_engine/ Write and AI will draw a picture.

Image to Image Demo: upload an image and AI will make a corresponding image: https://affinelayer.com/pixsrv/

3. Learn

A great introductory article as an overview: From IBM "A beginner’s guide to artificial intelligence, machine learning, and cognitive computing"

AI and ML for Kids

https://machinelearningforkids.co.uk/

https://machinelearningforkids.co.uk/#!/links

 https://medium.com/stempedia/ai-for-kids-teach-kids-ai-with-the-best-online-ai-course-26575ab57337

https://thestempedia.com/blog/teaching-ai-kids/

https://thestempedia.com/shop/online-courses/artificial-intelligence-for-kids/

8 AI-driven Creative Apps for You and Your Kids

https://towardsdatascience.com/8-ai-driven-creative-apps-for-you-and-your-kids-5fdd71407dc4



Google Youtube video "AI Adventures: What is Machine Learning"

This tutorial and list of ML algorithms might be helpful to learn from:

 https://data-flair.training/blogs/machine-learning-tutorial/

https://www.newtechdojo.com/list-machine-learning-algorithms/

Google Dialogflow tutorials -Try it free https://cloud.google.com/dialogflow

 Medium "The most impressive Youtube Channels for you to Learn AI, Machine Learning, and Data Science"

Python Profits:  Learn ML, Regression, Classification, DL, Big Data https://www.pythonprofits.com/

IBM Watson

FREE cognitiveclass.ai courses include docker, chatbots, cloud, ML, Python, Node-RED, blockchain, TJBot, Big Data, Hadoop, Data Science, R, Serverless computing, Iot, Data Visualization, DL, Istio, Swift, statistics, Spark, GPU, Tensorflow, SQL, Bitcoin, Scala, NoSQL, MapReduce, YARN, Graphx, Kubernetes K8s, OpenShift, Microservices, Predictive modeling, Kafka, zookeeper, Solr, and more. see https://cognitiveclass.ai/courses

Data Science courses https://community.ibm.com/community/user/datascience/coursera

Design Thinking course https://www.ibm.com/design/thinking/page/courses/Practitioner

AI: Deep Learning Course at NYU CDS (Center for Data Science) accessible to all: https://nyudatascience.medium.com/yann-lecuns-deep-learning-course-at-cds-is-now-fully-online-accessible-to-all-787ddc8bf0af

Microsoft

https://www.microsoft.com/en-us/research/group/deep-learning-group/

 Kaggle

https://www.kaggle.com/learn/intro-to-deep-learning

https://www.kaggle.com/learn/overview

https://jonathan-hui.medium.com/gan-some-cool-applications-of-gans-4c9ecca35900

Learn Python 

Python is considered by many to be the most popular language for AI.

For beginners (and children too), you can learn a bit about Python by using Turtle graphics. This was introduced to me by our local library which sponsored an Hour of Code and provided some of the following links:

https://hourofpython.com/  - Click on the "start learning" button for the free lesson of "Python with Turtles" - This might be fun to do with your friends or family too.

Python Turtle sandbox and documentation on how to use turtle and the beginner's guide to python turtle

If you want to learn python, here are some courses and tutorials

Beginners guide: https://wiki.python.org/moin/BeginnersGuide/NonProgrammers

https://www.learnpython.org/ 

Learn DL 

Or you can monitor a class on Coursera or edx.

AI Newsletter: https://thesequence.substack.com/ or https://thesequence.substack.com/p

Ivy League University Online Classes

https://qz.com/1821327/450-free-ivy-league-university-courses-you-can-take-online/

Georgia Tech Course on Machine Learning (need to create a free account):

https://classroom.udacity.com/courses/ud262AI Machine Learning Data Sets:

Data for AI:


Datacatalogs.org

Data.un.org

www.data.gov

europeandataportal.eu/en

Kaggle.com/datasets

Datasetsearch.research.google.com

Community Data License Agreement:

Cdla.io

AWS Data Exchange marketplace

Data Access Exchange: DAX: https://developer.ibm.com/exchanges/data/
Has data notebooks

Model Exchanges
Model zoos:  Pytorch, TensorFlow, Keras, ONYX

MAX – Model Asset Exchange 

https://developer.ibm.com/exchanges/models

When I presented the webinar, there were questions about Project Management and AI. I referred people to my previous webinar on "Project Management and Artificial Intelligence" and my blog post on "Project Management and Artificial Intelligence"

4. Use / Apply

Alexa Skills:  

Alexa has "Skill Blueprints" that can be set up fairly easily. For example, here is the Q&A skill blueprint you can use to have Alexa answer your questions with answers you want. More information in this article by CNBC "How to get Alexa to answer certain questions exactly how you want it to" Updated Thu, Apr 19 2018 by Todd Haselton @robotodd

Learn to program a skill (like an app) for Alexa: "What is the Alexa Skills Kit?"

Compete for good with AI: Kaggle Competitions include some benevolent uses of AI

"How to build a chatbot for your school in less than an hour" by Brooke Gleason on 08 APR 2020

AI Gaming - Competitions at programming bots to win games with bitcoin as the prize https://www.aigaming.com/

 5. Share / Use it for Good / For Benefit

AI for Good organization

Microsoft AI for Good

Google AI for Social Good

DataRobot - AI for Good - For Non-profits - Cohort program open until April 30, 2021 

 https://www.citizenai.nz/



 


Tuesday, May 05, 2020

Project Management and Artificial Intelligence

I am posting this as a supplement to several talks I'm giving on "Project Management and Artificial Intelligence"

I suggest you look at this previous blog post where I provided lots of information on AI and Project Management.


About AI:
Examples of AI:
  • Chatbots
  • Virtual Assistants: Alexa, Google Assistant, Siri, Cortana
  • RPA
  • Robots (e.g. Boston Dynamics and DARPA Robotics Challenge) and Cobots
  • Recommendation Engines: Amazon, Netflix, etc.
  • Gaming (Go, Chess, Jeopardy, video games)
  • Speech recognition and speech synthesis
  • NLP – analyzing documents/ Knowledge Base
  • Autonomous vehicles and semi-autonomous
  • Expert systems / Decision support systems
  • Medical diagnosis (oncology, radiology)
  • Visual recognition (including Facial recognition)
  • Spam filtering
  • Fraud detection
  • Digital Workers - e.g. ipsoft
  • Emerj.com : Everyday Examples of Artificial Intelligence and Machine Learning
Fields of AI:
Subfields of AI:

Types of AI
  •  Forbes (June 2019) : 7 Types Of Artificial Intelligence
    •  AI Classification
      • Classification based on likeness to Human Mind
        • Reactive machines – no memory. e,g, big blue that mastered chess
        • Limited memory - chatbots, self-driving cars, VAs
        • Theory of Mind -  understands needs, emotions, beliefs
        • Self-Aware - human-like intelligence and self-awareness
      • Technical Classification
        • Artificial Narrow Intelligence (ANI) aka Weak AI or Narrow AI: this is AI specialized in it's application area (e.g. what is available now)
        • Artificial General Intelligence (AGI) aka Stong AI: self-learning in general areas like a human - "Technical Singularity"
        • Artificial Superintelligence (ASI) – more than human
    • Medium:  Types of Machine Learning Algorithms You Should Know
      • Supervised Learning - Human does the teaching (labeled training)
      • Unsupervised learning - learns on it's own to mine data for rules, patterns and groupings
      • semi-supervised learning - lies between the two above: Human provides some training and the system extrapolates from there.
      • reinforcement learning - Human provides a "reinforcement signal" (a "goal") and the AI "agent" interacts with the environment to see which experiences optimize the reinforcement. This is used for Gaming (Go, Chess), and autonomous vehicles.
    • KDnuggets: AI Knowledge Map: How To Classify AI Technologies

About CAPTCHA
Testing AI:
  • Hold-Out (aka "Blind data") test set Vs. Cross-Validation - Medium
  • K-Fold Cross Validation - Wikipedia
Project Management and AI


Will AI take away my PM job?

I suggest you look at this previous blog post where I provided lots of information on AI and Project Management. 

What comments or additions do you have on this information?