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Module - 1
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What is Artificial Inetelligence
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What is Machine Learning
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What is Deep Learning
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What is Data Science
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What is Data Science
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Module - 2 - Numpy Introduction
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Introduction to Numpy
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How to create an Array in Numpy and different way to create an array
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Module - 3 - Indexing and Slicing
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Numpy Array Indexing
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Numpy Advanced Indexing
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Module-4 Different Data Types NumPy and Converting data types in python
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NumPy Data Types
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Module-4 Array Manipulation
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NumPy Array Shape
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NumPy Array Reshaping
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Module-5 Iteration over an Array
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NumPy Array Iterating
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Module-6 NumPy Joining the array
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NumPy Joining Array
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Splitting the Array in NumPy
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NumPy Splitting Array
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NumPy Array Search
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NumPy Searching Arrays
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NumPy Array Sort
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NumPy Sorting Arrays
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Module-7 Numpy-Random
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Random Introduction
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Normal Distribution "
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"2.Binomial Distribution "
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"3.poission Distribution "
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4.Uniform Distribution
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Module-8 Introduction
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Introducrion of Pandas
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Module-9 Pandas-Series
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How to creat a Pandas Series
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Module-10 Pnadas Data Frame
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How to create a pandas data frame and different ways to create data frame
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Data Frame Basic Functionality for Data Science
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Iterate over Pandas DataFrame
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"1.How to iterate over DataFrame 2.Iterate Using Index Method "
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3.Iterate Using loc function
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4.Iterate Using Iloc Function
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"4.Iterate Using iterrows method "
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5.Iterate Using itertuples Method
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Module-11 Handling Missing Values
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"Theory Session 1.What is Missing Values 2.How to impute the Misisng values"
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"Practical Session 3.How to find Missing value with various technique"
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4.Handling Missing value with Dropna Function.
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5.handle missing value in Numerical Data with fillna function
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6.handle and impute missing value on categorical Data with fillna Function
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7.Imputing missing value in Both Numerical and Categorical variable at once with Lambda Function
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7.Imputing missing value in Both Numerical and Categorical variable at once with Lambda Function
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Module-12 Sorting Data
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Pandas Sort DataFrame By single Column
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"Pandas Sort DataFrame By Multiple Column Sort Data Frame "
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Soritng by index in Ascending/ Descending Order
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Soritng by index in Ascending/ Descending Order
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Working with missing data when sorting
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Module-13 Guoup By In Pnadas
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How to Grouping the Data in Pnadas
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How to marge two DataFrame In Pnadas
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MatplotLib Tutorials
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"1.Introduction of Matplotlib 2.Matplotlib Plotting "
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3.Matplotlib Marker
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4. Matplotlib LIne
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5. Matplotlib set grid line
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6.Matplotlib set subplot
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7. Matplotlib Scatter Plot
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8. Matplotlib Bar Graph
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9. Matplotlib Histogram
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10. Matplotlib Pie Chart
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Statistics
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What is Statistics
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Types of Data in Data Science
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Understanding the difference between a population and a sample
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Measure of central Tendancy
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What is mean and How to calculate the mean
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What is Median How to calculate the median
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"The measure of the spread Whatares variance and standard deviation and how to calculate it?"
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Calculating and Understanding the covariance
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What is distribution
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Understand the Normal Distribution
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Understand the Standard Normal Distribution
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Working with Eastimator and Estimate
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Student T Distribution
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calculating confidence intervals within a population with an unknown variance
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Hypothesis Testing
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Test for the mean. Population variance known
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What is P-value why it is one of the most useful tools for data science
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Machine Learning
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What is Machine Learning
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What is Supervised Learning
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What is unsupervised learning
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"Importing the libraries importing the DataSet"
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How to Describe the Data
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Check Unique Value
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How to Filter the Data using loc and Iloc function
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Filter and Group the data groupby function
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Filter the data using iteration
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Filter the data using Crostab method
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Filter the data using Pivot table
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Find Missing value throgh graph
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Count the value through the countplot
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Find the skewness in the Data
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Find the outliers in the Data
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Encoding Categorical Data with one hot encodeing
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Encoding Categorical Data with one label encoding
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Splitting the dataset into the training set and test
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What is Regresion
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Simple Linear regression intution
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Simple Linear Regression Mathematical equation
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R-Square Mathematical Solution
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Simple Linear Regression Practical Session
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What is Multiple Linear Regression and It's assumption
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Multiple Linear Regression Practical Part 1
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Polynomial regression intituiion
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Polynomial Regression Practical Session
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Support Vector Machine Intition
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Support Vector Machine Practical Session
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Decision Tree intution
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Decision Tree Practical Session
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Random Forest Intution
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Random Forest Practical Session
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Logistic Regression Intution
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Logistic Regression Practical session
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KNN Regression Practical Session
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K means Practical session
Preview - Data Science & Machine Learning
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