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[Udemy] 100+ Exercises – Python – Data Science – scikit-learn – 2022
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What you’ll learn
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resolve over 100 workout routines in numpy, pandas and scikit-study
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take care of actual programming issues in knowledge science
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work with documentation and Stack Overflow
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assured teacher assist
Requirements
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completion of all programs within the Python Developer studying path
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completion of all programs within the Data Scientist studying path
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primary data of NumPy
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primary data of Pandas
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primary data of scikit-study and machine studying ideas
Description
Welcome to the 100+ Exercises – Python – Data Science – scikit-study course the place you possibly can take a look at your Python programming expertise in machine studying, particularly in scikit-study bundle.
Matters you’ll discover within the workout routines:
- getting ready knowledge to machine studying fashions
- working with lacking values, SimpleImputer class
- classification, regression, clustering
- discretization
- function extraction
- PolynomialFeatures class
- LabelEncoder class
- OneHotEncoder class
- StandardScaler class
- dummy encoding
- splitting knowledge into prepare and take a look at set
- LogisticRegression class
- confusion matrix
- classification report
- LinearRegression class
- MAE – Imply Absolute Error
- MSE – Imply Squared Error
- sigmoid() operate
- entorpy
- accuracy rating
- DecisionTreeClassifier class
- GridSearchCV class
- RandomForestClassifier class
- CountVectorizer class
- TfidfVectorizer class
- KMeans class
- AgglomerativeClustering class
- HierarchicalClustering class
- DBSCAN class
- dimensionality discount, PCA evaluation
- Affiliation Guidelines
- LocalOutlierFactor class
- IsolationForest class
- KNeighborsClassifier class
- MultinomialNB class
- GradientBoostingRegressor class
This course is designed for individuals who have primary data in Python, numpy, pandas and scikit-study. It consists of over 100 workout routines with options. It is a nice take a look at for people who find themselves studying machine studying and are on the lookout for new challenges. Exercises are additionally take a look at earlier than the interview. Many common subjects have been lined on this course.
Who this course is for:
- everybody who needs to study by doing
- everybody who needs to enhance Python programming expertise
- everybody who needs to enhance knowledge science expertise
- everybody who needs to enhance machine studying expertise