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AI For Good - Machine Learning For Kids

AI For Good - Machine Learning For Kids

AI For Good - Machine Learning For Kids


Nishan Chathuranga

November 07, 2020


  1. NISHAN CHATHURANGA Software Engineer 99X (Pvt) Ltd. University of Moratuwa

    Faculty of Information Technology WHO AM I
  2. AI FOR GOOD “Whether we are based on carbon or

    on silicon makes no fundamental difference; we should each be treated with appropriate respect.” - Sir Arthur C. Clarke (16 December 1917 – 19 March 2008), 2010: Odyssey Two GITHUB REPOS - github.com/MLforKids USING ARIMA MODEL - bit.ly/AIforGoodArima USING PROPHET LIBRARY - bit.ly/AIforGoodProphet
  3. AI FOR GOOD Lecture #1



  6. Understand the various ways AI can be used to make

    learning and life easier for the less privileged. Understand the severity of people’s actions and the toll it takes on the earth. > Learning Outcomes: AI for Earth
  7. How often have you heard that species of flora and

    fauna are facing extinction? Or forests are being cut down to create dwelling facilities? In the above-mentioned examples, we find that due to exploitation of the natural resources of the Earth, biodiversity is greatly affected. Animals, birds, insects are losing their habitats and are moving out of their designated areas. There are many areas on the Earth which are inhospitable for humans due to hostile climatic conditions. However, this cannot prevent us from conserving the flora and fauna at these places. AI FOR EARTH
  8. Using Satellite imagery for forest management Conserving our forests and

    what they contain (plants, animals, birds, insects etc.) will help us not only preserve its biodiversity but also help in tackling the challenges of global warming. It is essential to monitor our forests and the land they take up. Artificial Intelligence plays a particularly important role in such a scenario. Video: Mapping the future of our forests with Microsoft AI Satellite Imagery for Forest Management
  9. According to the University of British Columbia, “countries drastically underreport

    the number of fish caught worldwide. The new estimate, puts the annual global catch at roughly 109 million metric tons, about 30 per cent higher than the 77 million officially reported in 2010 by more than 200 countries and territories. This means that 32 million metric tons of fish goes unreported every year, more than the weight of the entire population of the United States”. Sustainability for Global Fishing
  10. Enabling Precision Conservation and Sustainable Agriculture Practices In today’s age,

    as resources become scarce, it is imperative to ensure that we use the available resources in the best and most efficient way possible. In order to achieve this goal, we should adopt sustainable agricultural practices such as precision farming or precision agriculture.
  11. Enabling Precision Conservation and Sustainable Agriculture Practices Another term that

    needs to be understood in the same context is precision agronomics. This means to provide accurate farming techniques for the planting and growing of crops, and involves the following. Variable Rate Technology GPS Soil Sampling Computer Based Applications Remote Sensing Technology It involves the following:
  12. Enabling Precision Conservation and Sustainable Agriculture Practices CIC Holdings PLC

    (CIC), recently announced their latest innovation, the use of agriculture drones for Precision Agriculture Practices – Smart Farming. The technology helps to scan fields and distribute agro chemicals and fertilizer with the minimum human involvement and wastage. This is the first time in the world that areas are being identified and automatically treated using the drone and GPS technology. https://www.cic.lk/ci c-introduces-smart- farming-to-sri-lanka/
  13. Enabling Precision Conservation and Sustainable Agriculture Practices How does precision

    farming benefit farmers, and why should they choose it over traditional ways of farming? Here are a few reasons which makes it amply clear as to why precision farming is more beneficial over the age-old methods of farming. Video: Drones, scanners and GPS all part of the 'precision farming' arsenal Increases agricultural productivity Prevents soil degradation Reduces the application of chemicals in crop production More efficient use of water resources Disseminates modern farm practices to improve quality, quantity and reduced cost of production Develops more favorable attitudes Changes the socio- economic status of farmers
  14. Climate Related Risk One of the many changes that we

    see happening is global warming and its impact on climate change. Climate change is one of the biggest challenges that the world has ever faced. The consequences are enormous and are affecting not only we humans but also flora and fauna globally.

  16. AI for Cultural Heritage Thinking of AI as a medium

    which changes our lives, what examples can you think of? Often the examples are chatbots, AI-powered personal digital assistants, apps working on sophisticated behavioural algorithms, AI-powered drones, self-driving cars, shopping bots, etc. AI is being used for the good of humanity in providing access and promoting a greater understanding of the rich and diverse cultural heritage of the bygone era.
  17. Preservation and Enrichment of Cultural Heritage around the World Oldest

    existing map engraved on this mammoth tusk, dated 25,000 BC In ancient times, going on a voyage was a matter of great concern as there were no maps. People had to rely on the North Star, the sun and the constellations to navigate. Though maps are known to have existed as early as 2300 BCE on Babylonian clay tablets, cartography became a full- fledged science only during the era of the Greeks. Ptolemy is one of the most prominent Greek astronomers and geographers of his time. It is he who created the first world map by depicting the ‘Old World’ from about 60°N to 30°S latitude. In France during the 17th and 18th centuries there was a trend of making 3D maps. These were large scale maps that were painstakingly precision built. Rulers of the time such as Napoleon and King Louis XVI considered them a strategic tool and as such kept them hidden from public view.
  18. Engaging with Communities around the World for Language Preservation Map

    by Ethnologue by SIL International In a world where more than 7000 languages are spoken, only a handful of languages are spoken by a large percentage of the population. One third of these languages have fewer than 1,000 people who continue to speak them. Segregation of languages according to EGIDS measurement tool
  19. Using Digital Tools to preserve Historical Artefacts, Paintings and other

    Works of Art According to the Internet Encyclopaedia of Philosophy, “Interpretation in art refers to the attribution of meaning to a work”. In order to interpret a work of art there are two prevalent concepts of isolationism and contextualism. Video: How Gen Studio was created for The Met using Microsoft AI Isolationism Contextualism
  20. DEMO Forecasting Future


    bit.ly/AIforGoodArima USING PROPHET LIBRARY - bit.ly/AIforGoodProphet
  22. Moving Average (Rolling Mean) A moving average helps cut down

    the amount of "noise" on a price chart. Look at the direction of the moving average to get a basic idea of which way the price is moving. If it is angled up, the y-variable is moving up (or was recently) overall; angled down, and the y-variable is moving down overall; moving sideways, and the y-variable is likely in a range. BASIC TERMINOLOGY
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  24. Stationarity In the most intuitive sense, stationarity means that the

    statistical properties of a process generating a time series do not change over time. It does not mean that the series does not change over time, just that the way it changes does not itself change over time. The algebraic equivalent is thus a linear function, perhaps, and not a constant one; the value of a linear function changes as grows, but the way it changes remains constant — it has a constant slope; one value that captures that rate of change. BASIC TERMINOLOGY
  25. ARIMA Model An Autoregressive Integrated Moving Average (ARIMA) model is

    a generalization of an autoregressive moving average (ARMA) model. Both of these models are fitted to time series data either to better understand the data or to predict future points in the series (forecasting). The AR part of ARIMA indicates that the evolving variable of interest is regressed on its own lagged (i.e., prior) values. The MA part indicates that the regression error is actually a linear combination of error terms whose values occurred contemporaneously and at various times in the past. The I (for "integrated") indicates that the data values have been replaced with the difference between their values and the previous values BASIC TERMINOLOGY
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