tusharkholia Goto Github PK
Name: tushar kholia
Type: User
Company: Student
Bio: :)
Twitter: tushar_kholia
Location: India
Blog: https://www.kholia.org
Name: tushar kholia
Type: User
Company: Student
Bio: :)
Twitter: tushar_kholia
Location: India
Blog: https://www.kholia.org
sample app for nothing
Barack Obama is left-handed. So are Bill Gates and Oprah Winfrey; so were Babe Ruth and Marie Curie. A 1991 study reported that left-handed people die on average nine years earlier than right-handed people. Nine years! Could this really be true? In this project, you will explore this phenomenon using age distribution data to see if we can reproduce a difference in average age at death purely from the changing rates of left-handedness over time, refuting the claim of early death for left-handers. This notebook uses pandas and Bayesian statistics to analyze the probability of being a certain age at death given that you are reported as left-handed or right-handed. This project lets you apply the skills from pandas Foundations, Statistical Thinking in Python, Introduction to Data Visualization with Python, and concepts from Foundations of Probability in R and Fundamentals of Bayesian Data Analysis in R, including reading data, creating new columns, creating matplotlib visualizations, using numpy arrays, constructing probabilities from frequency data, and Bayes' theorem. We recommend that you take those courses before starting this project.
ecommerce marketing
To better understand the growth and impact of Bitcoin and other cryptocurrencies you will, in this project, explore the market capitalization of different cryptocurrencies. Warning: The cryptocurrency market is exceptionally volatile, and any money you put in might disappear into thin air. Never invest money you can't afford to lose. To complete this project, you need to be fluent with pandas DataFrames. Before starting this project, we recommend that you have completed the following courses: pandas Foundations Manipulating DataFrames with pandas Cleaning Data in Python
☁️ A simple one page marketing site starter for SaaS companies and indie hackers
it is a sample content which contains a sample project
A recommender system is a simple algorithm whose aim is to provide the most relevant information to a user by discovering patterns in a dataset. The algorithm rates the items and shows the user the items that they would rate highly. An example of recommendation in action is when you visit Amazon and you notice that some items are being recommended to you or when Netflix recommends certain movies to you. They are also used by Music streaming applications such as Spotify and Deezer to recommend music that you might like.
When you assess whether to invest in an asset, you want to look not only at how much money you could make but also at how much risk you are taking. The Sharpe Ratio, developed by Nobel Prize winner William Sharpe some 50 years ago, does precisely this: it compares the return of an investment to that of an alternative and relates the relative return to the risk of the investment, measured by the standard deviation of returns. In this project, you will apply the Sharpe ratio to real financial data using pandas.
My github landing page
This project is made by keeping in mind that it is to be used over the network, which can facilitate ease of shopping. So far as future scope of the project is concerned, firstly it is open to any modular expansion i.e. other modules or functions can be designed and embedded to handle the user need in future. Any part of the software and reports can be modified independently without much effort.
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