Completed my project 1 .Takes lot of reference from the videos and some google help to complete the project.

Completed both my project.It's really interesting project to work and learned many things while doing this two projects.

    Attached all the Screenshots for references.  It's really an interest project to work on . After learning the 6 week of courses I can able to do the project in given time .

  It's really an interesting project to work on. Learned lot of new things in this project.

Completed my Project 1 of Data Cleaning and Transformation using Pivot table and Charts for the Report on requirement of Team Hiring. It's really an interesting project to work on . 

https://docs.google.com/spreadsheets/d/1orT81ODgBPHIKX2PAXqP1yboHUPraO6c/edit?usp=share_link&ouid=114421097437687925364&rtpof=true&sd=true (or) https://docs.google.com/spreadsheets/d/1xrxx031tLSSDp7BHTMU4CzT7kaTGMqG7/edit?usp=share_link&ouid=114421097437687925364&rtpof=true&sd=true   Both are…

https://public.tableau.com/views/WorkinSTEMfield/WorkinSTEMfield?:language=en-US&:display_count=n&:origin=viz_share_link Completed my Tableau Project 1.

https://public.tableau.com/views/Project2_16692158211520/Dashboard1?:language=en-US&publish=yes&:display_count=n&:origin=viz_share_link Completed my tableau Project 2.

Submitted my project 1.

Completed my Project 2.

Q1. The data is about insurance details of all the customers . It belongs to Supervised learning because it has both input and output variable in the data. It deals with the Regression in Supervised learning ,so by seeing the data we can conclude it is Supervised learning. Q3. The data is cleaned there is no null values…

Q10. Ans: No. Alcohol level is, everything else being equal, mainly a result of the amount of sugar in the grapes. Warmer climates tend to allow for higher alcohol levels as the growing season is often longer. As an example, California wines tend to be relatively high in alcohol, 14.5% being no exception. Burgundy on the…

Q1.  In statistics, we take a sample of a population and say that the sample mean and sample variance are the same as the population mean and variance. If we repeat this process many times by taking a different (but same sized) sample each time and averaged the results the result for the mean would indeed be close…

Q2. Ans: The applicablity of simple mean and expected value are dependent on the nature of the case study. In smaller case studies where the random variable outcomes can be measured as frequency of occurences or each observation in the sample can be noted, the simple mean is calculated as Sum of all observations/number…

Q1. Ans: To perform gradient descent in python using mean square error as loss function on the following data set: y = [1,2,3,4,5]x = [0,1,2,3,4] Theory: Loss function: J = (1n)∑(y(i)−(mx(i)+b))2(1n)∑(y(i)-(mx(i)+b))2, where x(i) are the input m and b are the weights  mx(i)+b is the predicted…

Q1. Ans: Advantages: SVM works relatively well when there is a clear margin of separation between classes. SVM is more effective in high dimensional spaces. SVM is effective in cases where the number of dimensions is greater than the number of samples. SVM is relatively memory efficient Disadvantages: SVM algorithm is…

Q2. Advantage: It's easy to understand and simple to implement It can be used for both classification and regression problems It's ideal for non-linear data since there's no assumption about underlying data It can naturally handle multi-class cases It can perform well with enough representative data Diadvantage: Associated…

Q1.Ans: A neural network is a series of algorithms that endeavors to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates. In this sense, neural networks refer to systems of neurons, either organic or artificial in nature. Neural networks can adapt to changing…

Q1.Ans: Similarity in categorical data is not as direct when it comes to numerical data. The categorical data is first tranformed to numerical values and both are standardised to make sense of the similarity and dissimilarity between/among those features.

Completed the Project1.

Completed the project 2.

Aim The aim of this project is to analyze the data in detail on vaccinated people and fully vaccinated people by country in 2021-2022 Introduction Since the start of the COVID-19 outbreak, WHO has worked with countries and areas in Different regions on public health measures to slow or stop the spread of the virus. Safe…

Aim The aim of this project is to collect and analyze the data in detail of the Pickup point of the Airport and City Request id in Uber Request Data.   Introduction Uber provides the 2016 data. By using this data find out the demand and supply Analysis gap of the cab. The main objective of this project is to analyze…

Completed the Project1