100+ Exercises – Python – Data Science – Scikit-learn – 2023

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What you will learn

solve over 100 exercises in numpy, pandas and scikit-learn

deal with real programming problems in data science

work with documentation and Stack Overflow

guaranteed instructor support

Description

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RECOMMENDED LEARNING PATH

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COURSE DESCRIPTION

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100+ Exercises – Python – Data Science – scikit-learn


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Welcome to the course 100+ Exercises – Python – Data Science – scikit-learn where you can test your Python programming skills in machine learning, specifically in scikit-learn package.

 

Topics you will find in the exercises:

  • preparing data to machine learning models

  • working with missing values, SimpleImputer class

  • classification, regression, clustering

  • discretization

  • feature extraction

  • PolynomialFeatures class

  • LabelEncoder class

  • OneHotEncoder class

  • StandardScaler class

  • dummy encoding

  • splitting data into train and test set

  • LogisticRegression class

  • confusion matrix

  • classification report

  • LinearRegression class

  • MAE – Mean Absolute Error

  • MSE – Mean Squared Error

  • sigmoid() function

  • entorpy

  • accuracy score

  • DecisionTreeClassifier class

  • GridSearchCV class

  • RandomForestClassifier class

  • CountVectorizer class

  • TfidfVectorizer class

  • KMeans class

  • AgglomerativeClustering class

  • HierarchicalClustering class

  • DBSCAN class

  • dimensionality reduction, PCA analysis

  • Association Rules

  • LocalOutlierFactor class

  • IsolationForest class

  • KNeighborsClassifier class

  • MultinomialNB class

  • GradientBoostingRegressor class

This course is designed for people who have basic knowledge in Python, numpy, pandas and scikit-learn. It consists of over 100 exercises with solutions.

This is a great test for people who are learning machine learning and are looking for new challenges. Exercises are also a good test before the interview. Many popular topics were covered in this course.

 

If you’re wondering if it’s worth taking a step towards Python, don’t hesitate any longer and take the challenge today.

English
language

Content

Configuration (optional)

Intro
Info
Google Colab + Google Drive
Google Colab + GitHub
Google Colab – Intro
Anaconda installation – Windows 10
Introduction to Spyder
Anaconda installation – Linux

Tips

Intro
A few words from the author

Starter

Exercise 0
Solution 0

Exercises 1-10

Exercise 1
Solution 1
Exercise 2
Solution 2
Exercise 3
Solution 3
Exercise 4
Solution 4
Exercise 5
Solution 5
Exercise 6
Solution 6
Exercise 7
Solution 7
Exercise 8
Solution 8
Exercise 9
Solution 9
Exercise 10
Solution 10

Exercises 11-20

Exercise 11
Solution 11
Exercise 12
Solution 12
Exercise 13
Solution 13
Exercise 14
Solution 14
Exercise 15
Solution 15
Exercise 16
Solution 16
Exercise 17
Solution 17
Exercise 18
Solution 18
Exercise 19
Solution 19
Exercise 20
Solution 20

Exercises 21-30

Exercise 21
Solution 21
Exercise 22
Solution 22
Exercise 23
Solution 23
Exercise 24
Solution 24
Exercise 25
Solution 25
Exercise 26
Solution 26
Exercise 27
Solution 27
Exercise 28
Solution 28
Exercise 29
Solution 29
Exercise 30
Solution 30

Exercises 31-40

Exercise 31
Solution 31
Exercise 32
Solution 32
Exercise 33
Solution 33
Exercise 34
Solution 34
Exercise 35
Solution 35
Exercise 36
Solution 36
Exercise 37
Solution 37
Exercise 38
Solution 38
Exercise 39
Solution 39
Exercise 40
Solution 40

Exercises 41-50

Exercise 41
Solution 41
Exercise 42
Solution 42
Exercise 43
Solution 43
Exercise 44
Solution 44
Exercise 45
Solution 45
Exercise 46
Solution 46
Exercise 47
Solution 47
Exercise 48
Solution 48
Exercise 49
Solution 49
Exercise 50
Solution 50

Exercises 51-60

Exercise 51
Solution 51
Exercise 52
Solution 52
Exercise 53
Solution 53
Exercise 54
Solution 54
Exercise 55
Solution 55
Exercise 56
Solution 56
Exercise 57
Solution 57
Exercise 58
Solution 58
Exercise 59
Solution 59
Exercise 60
Solution 60

Exercises 61-70

Exercise 61
Solution 61
Exercise 62
Solution 62
Exercise 63
Solution 63
Exercise 64
Solution 64
Exercise 65
Solution 65
Exercise 66
Solution 66
Exercise 67
Solution 67
Exercise 68
Solution 68
Exercise 69
Solution 69
Exercise 70
Solution 70

Exercises 71-80

Exercise 71
Solution 71
Exercise 72
Solution 72
Exercise 73
Solution 73
Exercise 74
Solution 74
Exercise 75
Solution 75
Exercise 76
Solution 76
Exercise 77
Solution 77
Exercise 78
Solution 78
Exercise 79
Solution 79
Exercise 80
Solution 80

Exercises 81-90

Exercise 81
Solution 81
Exercise 82
Solution 82
Exercise 83
Solution 83
Exercise 84
Solution 84
Exercise 85
Solution 85
Exercise 86
Solution 86
Exercise 87
Solution 87
Exercise 88
Solution 88
Exercise 89
Solution 89
Exercise 90
Solution 90

Exercises 91-100

Exercise 91
Solution 91
Exercise 92
Solution 92
Exercise 93
Solution 93
Exercise 94
Solution 94
Exercise 95
Solution 95
Exercise 96
Solution 96
Exercise 97
Solution 97
Exercise 98
Solution 98
Exercise 99
Solution 99
Exercise 100
Solution 100

Exercises 100+

Exercise 101
Solution 101
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