Tensorflow and Ai Basic Flashcards
Whatever information we always have that we need to give to the model to get some output is what we call our _____
a. features
b. labels
c. neurons
a. features
Features - Whatever information we always have that we need to give to the model to get some output
Ex.
Midterm 1 Midterm 2 Final
70 ? 77
Midterm 1 and Final are features
Midterm 2 is a Label (What we are trying to predict.
The information we are trying to predict or looking for.
a. features
b. labels
c. neurons
b. labels
Labels - Information we are trying to predict or looking for.
When we feed our features to a model we will get out the label.
Ex.
Midterm 1 Midterm 2 Final
70 ? 77
Midterm 1 and Final are features
Midterm 2 is a Label (What we are trying to predict.)
_______ We have features and labels.
It makes a prediction using the rules and makes an arbitrary prediction using the rules it already knows, then compares that prediction it made to the arbitrary prediction.
a. Supervised Learning
b. Unsupervised Learning
c. Reinforcement Learning
a. Supervised Learning
We have features and labels.
It makes a prediction using the rules and makes an arbitrary prediction using the rules it already knows, then compares that prediction it made to the arbitrary prediction.
Steps of Supervised Learning Works
- Have features and labels
- You pass the features
- The model has some rules and its already built
- It makes a prediciton
- Then compares that prediction to the label then retweaks the model
- Continues to retweak with 1000s upon 1000s of data.
Steps of Supervised Learning Works
- Have features and labels
- You pass the features
- The model has some rules and its already built
- It makes a prediciton
- Then compares that prediction to the label then retweaks the model
- Continues to retweak with 1000s upon 1000s of data.
The most common type of learning
a. Supervised Learning
b. Unsupervised Learning
c. Reinforcement Learning
a. Supervised Learning
Supervised Learning- The most common type of learning
_______ This type of learning only has Features. No labels or no output for these features. You want the model to figure out the output for you.
a. Supervised Learning
b. Unsupervised Learning
c. Reinforcement Learning
b. Unsupervised Learning
Unsupervised learning only has Features. No labels or no output for these features. You want the model to figure out the output for you.
Steps for Unsupervised Learnings
-Want the model to create clusters or groups.
_______ You do not have any data. You have an agent, an environment, and a reward. Objective is to maximize the reward.
a. Supervised Learning
b. Unsupervised Learning
c. Reinforcement Learning
c. Reinforcement Learning
Reinforcement Learning- A type of learning where you do not have any data. You have an agent, an environment, and a reward. Objective is to maximize the reward.
_____ is a datapoint
a. tensor
b. vector
c. panda
b. vector
vector - is a datapoint
___ tells what kind of information is in the tensor.
a. data type
b. float32, int32, string
c. data shape
d. both a and b
d. both a and b
data type - tells what kind of information is in the tensor.
Float32, int32, or string are examples of datatype
what means 1 number in TensorFlow?
a. vector
b. tensor
c. scalor
c. scalar
scalar- mean 1 number in tensorflow
____ tells you how many dimensions you have.
a. tensor.shape
b. tensor. vector
c. tf.variable
a. tensor.shape - tells you how many dimensions you have.
ex. if you have 2 lists and use tf.shape you will have
(2,2)
if you have 3 lists [],[],[] then use tensor.shape you would have (3,3)
To evaluation a tensor you need to do _____
a. tf.session()
b. tf.shape
c. tf.tensorflow
a. tf.session()
to evaluate a tensor you need to use a session. by tf.session() you
