Course Content
1.
Accuracy Score
0 min
2 min
0
2.
Activation Function
0 min
2 min
0
3.
Algorithm
0 min
2 min
0
4.
Assignment Operator (Python)
0 min
2 min
0
5.
Artificial General Intelligence (AGI)
0 min
3 min
0
6.
Artificial Intelligence
0 min
4 min
0
7.
Artificial Narrow Intelligence (ANI)
0 min
3 min
0
8.
Artificial Neural Network (ANN)
0 min
2 min
0
9.
Backpropagation
0 min
2 min
0
10.
Bias
0 min
2 min
0
11.
Bias-Variance Tradeoff
0 min
2 min
0
12.
Big Data
0 min
2 min
0
13.
Business Analyst (BA)
0 min
2 min
0
14.
Business Analytics (BA)
0 min
2 min
0
15.
Business Intelligence (BI)
0 min
1 min
0
16.
Categorical Variable
0 min
1 min
0
17.
Clustering
0 min
2 min
0
18.
Command Line
0 min
1 min
0
19.
Computer Vision
0 min
2 min
0
20.
Continuous Variable
0 min
1 min
0
21.
Cost Function
0 min
2 min
0
22.
Cross-Validation
0 min
2 min
0
23.
Data Analysis
0 min
7 min
0
24.
Data Analyst
0 min
4 min
0
25.
Data Science
0 min
1 min
0
26.
Data Scientist
0 min
6 min
0
27.
Early Stopping
0 min
2 min
0
28.
Exploratory Data Analysis (EDA)
0 min
2 min
0
29.
False Negative
0 min
1 min
0
30.
False Positive
0 min
1 min
0
31.
Google Colaboratory
0 min
2 min
0
32.
Gradient Descent
0 min
2 min
0
33.
Hidden Layer
0 min
2 min
0
34.
Hyperparameter
0 min
2 min
0
35.
Image Recognition
0 min
2 min
0
36.
Imputation
0 min
2 min
0
37.
K-fold Cross Validation
0 min
2 min
0
38.
K-Means Clustering
0 min
2 min
0
39.
Linear Regression
0 min
2 min
0
40.
Logistic Regression
0 min
1 min
0
41.
Machine Learning Engineer (MLE)
0 min
5 min
0
42.
Mean
0 min
2 min
0
43.
Neural Network
0 min
2 min
0
44.
Notebook
0 min
3 min
0
45.
One-Hot Encoding
0 min
2 min
0
46.
Operand
0 min
1 min
0
47.
Operator (Python)
0 min
1 min
0
48.
Print Function (Python)
0 min
1 min
0
49.
Python
0 min
5 min
0
50.
Quantile
0 min
1 min
0
51.
Quartile
0 min
1 min
0
52.
Random Forest
0 min
2 min
0
53.
Recall
0 min
2 min
0
54.
Scalar
0 min
2 min
0
55.
Snake Case
0 min
1 min
0
56.
T-distribution
0 min
2 min
0
57.
T-test
0 min
2 min
0
58.
Tableau
0 min
2 min
0
59.
Target
0 min
1 min
0
60.
Tensor
0 min
2 min
0
61.
Tensor Processing Unit (TPU)
0 min
2 min
0
62.
TensorBoard
0 min
2 min
0
63.
TensorFlow
0 min
2 min
0
64.
Test Loss
0 min
2 min
0
65.
Time Series
0 min
2 min
0
66.
Time Series Data
0 min
2 min
0
67.
Test Set
0 min
2 min
0
68.
Tokenization
0 min
2 min
0
69.
Train Test Split
0 min
2 min
0
70.
Training Loss
0 min
2 min
0
71.
Training Set
0 min
2 min
0
72.
Transfer Learning
0 min
2 min
0
73.
True Negative (TN)
0 min
1 min
0
74.
True Positive (TP)
0 min
1 min
0
75.
Type I Error
0 min
2 min
0
76.
Type II Error
0 min
2 min
0
77.
Underfitting
0 min
2 min
0
78.
Undersampling
0 min
2 min
0
79.
Univariate Analysis
0 min
2 min
0
80.
Unstructured Data
0 min
2 min
0
81.
Unsupervised Learning
0 min
2 min
0
82.
Validation
0 min
2 min
0
83.
Validation Loss
0 min
1 min
0
84.
Vanishing Gradient Problem
0 min
2 min
0
85.
Validation Set
0 min
2 min
0
86.
Variable (Python)
0 min
1 min
0
87.
Variable Importances
0 min
2 min
0
88.
Variance
0 min
2 min
0
89.
Variational Autoencoder (VAE)
0 min
2 min
0
90.
Weight
0 min
1 min
0
91.
Word Embedding
0 min
2 min
0
92.
X Variable
0 min
2 min
0
93.
Y Variable
0 min
2 min
0
94.
Z-Score
0 min
1 min
0
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In Python, a variable is a named location in memory that stores a value. It can hold different types of data such as numbers, strings, lists, tuples, or even complex objects.
To create a variable in Python, you need to assign a value to it using the equal sign (=). For example, you can create a variable called x and assign it the value of 5 as follows:
In this case, Python creates a new variable called x and assigns it the value of 5. You can then use this variable in your program to perform various operations. For example, you can print the value of x using the print() function as follows:
5This will output the value of x, which is 5, to the output section of the code cell.
You can also update the value of a variable at any time by assigning a new value to it. For example, you can update the value of x to 10 as follows:
10In this case, Python updates the value of x to 10 and stores it in the same memory location previously allocated for x.