https://padlet.com/liviafragosopi/md6d77wxhcp2fi4q en-us 2021-02-04 00:27:16 UTC 2025-12-12 13:32:53 UTC hello@padlet.com https://padlet-uploads.storage.googleapis.com/659605399/fb3d15ea1c509bf5a3ebc0caf49fb39b/udacity.png liviafragosopi https://padlet.com/liviafragosopi/md6d77wxhcp2fi4q/wish/1161492452 AI: "The science and engineering of making computers behave in ways that, until recently, we thought required human intelligence." Andrew Moore.

Applications: Face recognition, text recognition, speech recognition, computer vision, recognition of mechanical failures, NPL, etc.

Extra sources: ]]> 2021-02-04 00:27:47 UTC https://padlet.com/liviafragosopi/md6d77wxhcp2fi4q/wish/1161492452 liviafragosopi https://padlet.com/liviafragosopi/md6d77wxhcp2fi4q/wish/1161492934 AI integrates perception, prediction, and decision-making]]> 2021-02-04 00:28:01 UTC https://padlet.com/liviafragosopi/md6d77wxhcp2fi4q/wish/1161492934 liviafragosopi https://padlet.com/liviafragosopi/md6d77wxhcp2fi4q/wish/1161537692 Sectors with great potential:

* Retail: pricing, promotion, and customer service management
*Consumer goods: supply-chain management, demand forecasting
*Finance: marketing and sales, assessing and managing risks.

Example: Blue River technology - using computer vision, their tractors can only spread herbicide on weeds, and not the crops.

Extra sources:]]> 2021-02-04 00:50:21 UTC https://padlet.com/liviafragosopi/md6d77wxhcp2fi4q/wish/1161537692 liviafragosopi https://padlet.com/liviafragosopi/md6d77wxhcp2fi4q/wish/1161549962 What is ML?

"Computer algorithms that improve automatically trough experience." - Tom Mitchel

ML Techniques:
* Supervised Learning:
Maps an input to an output. It uses a training set to teach models to yield the desired output. This training dataset includes inputs and correct outputs.
* Unsupervised Learning:
The training set is unlabeled.  These algorithms discover hidden patterns or data groupings without the need for human intervention
* Reinforcement Learning
The learning system (agent) observes the context, selects and performs actions based on the possibility of gaining rewards (or penalties, i.e., negatives rewards). It learns by itself what is the best strategy, called policy, to get the most reward over time.

Extra sources:
Check this Mindmap:

]]> 2021-02-04 00:56:31 UTC https://padlet.com/liviafragosopi/md6d77wxhcp2fi4q/wish/1161549962 liviafragosopi https://padlet.com/liviafragosopi/md6d77wxhcp2fi4q/wish/1161555195 Artificial neural networks (ANNs) are comprised of node layers, containing an input layer, one or more hidden layers, and an output layer. Each node, or artificial neuron, connects to another and has an associated weight and threshold. If the output of any individual node is above the specified threshold value, that node is activated, sending data to the next layer of the network. Otherwise, no data is passed along to the next layer of the network.]]> 2021-02-04 00:58:49 UTC https://padlet.com/liviafragosopi/md6d77wxhcp2fi4q/wish/1161555195 liviafragosopi https://padlet.com/liviafragosopi/md6d77wxhcp2fi4q/wish/1161556788 "The opportunities are endless, as massive changes in methods can be brought to life by any unique mind, debates on AI and data ethics will continue, and businesses will rely more and more on these methods as their most valuable resource. Taking the time to understand where we came from and where we are going can allow everyone to develop their own vision of the future. The global matrix of these unique human visions is what will lead us into a bright future with AI at our side." Source: https://towardsdatascience.com/the-state-of-ai-in-2020-1f95df336eb0]]> 2021-02-04 00:59:33 UTC https://padlet.com/liviafragosopi/md6d77wxhcp2fi4q/wish/1161556788 liviafragosopi https://padlet.com/liviafragosopi/md6d77wxhcp2fi4q/wish/1166735261 It can process and learn from much more data than previous approaches.

Why is AI so relevant now?
1. Compute power
2. Data availability
3. Lower cost

Extra sources: Andrew Ng's Deep Learning course chart:

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