100+ Exercises - Python - Data Science - scikit-learn, Improve your machine learning skills and solve over 100 exercises in python, numpy, pandas and scikit-learn!
- Bestseller
- Created by Paweł Krakowiak
- English
What you'll 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
Requirements
- completed course '200+ Exercises - Programming in Python - from A to Z'
- completed course '210+ Exercises - Python Standard Libraries - from A to Z'
- completed course '150+ Exercises - Object Oriented Programming in Python - OOP'
- completed course '100+ Exercises - Python Programming - Data Science - NumPy'
- completed course '100+ Exercises - Python Programming - Data Science - Pandas'
- basic knowledge of scikit-learn and machine learning concepts
Description
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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
110+ Exercises - Python + SQL (sqlite3) - SQLite Databases
250+ Questions - Job Interview - Python Developer
SQL DEVELOPER:
SQL Bootcamp - Hands-On Exercises - SQLite - Part I
SQL Bootcamp - Hands-On Exercises - SQLite - Part II
110+ Exercises - Python + SQL (sqlite3) - SQLite Databases
200+ Questions - Job Interview - SQL Developer
JOB INTERVIEW SERIES:
250+ Questions - Job Interview - Python Developer
200+ Questions - Job Interview - SQL Developer
200+ Questions - Job Interview - Software Developer - Git
200+ Questions - Job Interview - Data Scientist
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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 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.
Who this course is for:
- everyone who wants to learn by doing
- everyone who wants to improve their Python programming skills
- everyone who wants to improve their data science skills
- everyone who wants to improve their machine learning skills
- everyone who wants to prepare for an interview
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