Basics of ML & AL Week 2 Challenge

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Ans 1. When the data is categorical, traditional similarity measures like Euclidean distance are not suitable because they rely on numeric values.Here are some common techniques:a) Binary (0/1) Encoding:- Convert categorical variables into binary vectors using one-hot encoding or label encoding. Then, calculate…

Ans 1. A Neural Network is a computational model inspired by the way biological neural networks in the human brain work. It is a type of ML algorithm used primarily for pattern recognition, data classification, and regression tasks.Ans 2. Deep learning is a subset of machine learning that focuses on algorithms…

Ans 2. Pros:            a) Simple to implement.            b) KNN can be used for classification, regression, and feature selection tasks.            c) KNN can handle non-linear relationships between features.   …

Ans 1. Pros:               a) SVM works well when there is a large number of features.            b) SVM can handle non-linear relationships between features and tagets.            c) SVM tries to find a hyperplane…

Ans 2. L1 regularization penalizes the sum of absolute values of the weights, whereas L2 regularization            penalizes the sum of squares of the weights.      …

Ans 2. In case of infinite number of Observations, it is very difficult to note each and every outcome. In such cases the probability of each outcome is determined using this probability. The formula is :                            μ=∑x⋅P(x)μ=∑x⋅P(x)Simple…

Ans 1.  Population variance: Uses N because you're working with the full dataset, no bias.                                                          σ2=∑(xi​−μ)^2/N​ …

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Q2. users_data.csv file succesfully imported in ecommerce Schema.  

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1. Public sub pdf() Dim x As workbook Dim y As worksheet Dim rng As Range Dim Path As String Dim FName As String set x=thisworkbook set y=x.worksheets("Report output") set rng=y.Range("D3:D19") Path= "G:\EXCEL\" FName="excel1" & ".pdf" rng.ExportAsFixedFormat _  type:=xltypepdf, Filename:=Path & FName, _ IgnorPrintAreas:=…

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