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--- computer_science:machine_learning:coursera:introduction_tensorflow_artificial_intelligence_deep [2020/08/10 12:46] – carlossousa
+++ computer_science:machine_learning:coursera:introduction_tensorflow_artificial_intelligence_deep [2023/12/01 12:07] (current) – external edit 127.0.0.1
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 As you work with neural networks, you'll see this pattern recurring. You will almost always deal with probabilities, not certainties, and will do a little bit of coding to figure out what the result is based on the probabilities, particularly when it comes to classification.
+==== Week 1 Quiz ====
+**The diagram for traditional programming had Rules and Data In, but what came out?** Answers
+**The diagram for Machine Learning had Answers and Data In, but what came out?** Rules
+**When I tell a computer what the data represents (i.e. this data is for walking, this data is for running), what is that process called? **Labelling the Data
+**What is a Dense? **A layer of connected neurons
+**What does a Loss function do?** Measures how good the urrent 'guess' is
+**What does the optimizer do?** Generates a new and improved guess
+**What is Convergence?** The process of getting very close to the correct answer
+**What does model.fit do?** It trains the neural network to fit one set of values to another
 ===== External References: =====