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100 Days of Code: Data Scientist Challenge 2022


Take the 100 days of code problem! Welcome to the 100 Days of Code: Data Scientist Challenge course the place you may take a look at your Python programming and information science expertise.

Subjects you can find within the workout routines:

  • working with numpy arrays

  • producing numpy arrays

  • producing numpy arrays with random values

  • iterating by arrays

  • coping with lacking values

  • working with matrices

  • studying/writing recordsdata

  • becoming a member of arrays

  • reshaping arrays

  • computing primary array statistics

  • sorting arrays

  • filtering arrays

  • picture as an array

  • linear algebra

  • matrix multiplication

  • determinant of the matrix

  • eigenvalues and eignevectors

  • inverse matrix

  • shuffling arrays

  • working with polynomials

  • working with dates

  • working with strings in array

  • fixing methods of equations

  • working with Sequence

  • working with DatetimeIndex

  • working with DataFrames

  • studying/writing recordsdata

  • working with totally different information sorts in DataFrames

  • working with indexes

  • working with lacking values

  • filtering information

  • sorting information

  • grouping information

  • mapping columns

  • computing correlation

  • concatenating DataFrames

  • calculating cumulative statistics

  • working with duplicate values

  • getting ready information to machine studying fashions

  • dummy encoding

  • working with csv and json filles

  • merging DataFrames

  • pivot tables

  • getting ready information 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 information into practice 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 and information science. It consists of 300 workout routines with options. It is a nice take a look at for individuals who need to change into an information scientist and are in search of new challenges. Workouts are additionally a great take a look at earlier than the interview.

When you’re questioning if it is price taking a step in the direction of information science, do not hesitate any longer and take the problem as we speak.

Stack Overflow Developer Survey

In keeping with the Stack Overflow Developer Survey 2021, Python is essentially the most needed programming language. Python handed SQL to change into our third hottest know-how. Python is the language builders need to work with most in the event that they aren’t already doing so.



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