4.59 (45 reviews)

Regular Price

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

**------------------------------------------------------------------------------**

**RECOMMENDED LEARNING PATH**

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**PYTHON DEVELOPER:**

200+ Exercises - Programming in Python - from A to Z

210+ Exercises - Python Standard Libraries - from A to Z

150+ Exercises - Object Oriented Programming in Python - OOP

150+ Exercises - Data Structures in Python - Hands-On

100+ Exercises - Advanced Python Programming

100+ Exercises - Unit tests in Python - unittest framework

100+ Exercises - Python Programming - Data Science - NumPy

100+ Exercises - Python Programming - Data Science - Pandas

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

250+ Exercises - Data Science Bootcamp in Python

**SQL DEVELOPER:**

SQL Bootcamp - Hands-On Exercises - SQLite - Part I

SQL Bootcamp - Hands-On Exercises - SQLite - Part II

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**COURSE DESCRIPTION**

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

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*classclassification, regression, clustering

discretization

feature extraction

*PolynomialFeatures*class*LabelEncoder*class*OneHotEncoder*class*StandardScaler*classdummy encoding

splitting data into train and test set

*LogisticRegression*classconfusion matrix

classification report

*LinearRegression*class*MAE*- Mean Absolute Error*MSE*- Mean Squared Error*sigmoid()*functionentorpy

accuracy score

*DecisionTreeClassifier*class*GridSearchCV*class*RandomForestClassifier*class*CountVectorizer*class*TfidfVectorizer*class*KMeans*class*AgglomerativeClustering*class*HierarchicalClustering*class*DBSCAN*classdimensionality reduction,

*PCA*analysisAssociation 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.

Screenshots

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

Reviews

I

Ivar13 August 2021

The course is perfect! I was looking for more than a year for a all-in-one-place course to hone your python skills (for SQL there are alternatives). Of course, you can find similar exercises across the web, but for $10 you have everything curated and easy to access. I'm going to get of data-science related courses as well. Dziekuje bardzo!

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