Curated Video
Introduction to FinTech Using R - How to Time Stock Market
In this video, you will learn how to time the stock market and will focus on the coding aspect of how the algorithm is designed. This clip is from the chapter "Stock Market Timing" of the series "Introduction to FinTech Using R".In this...
Curated Video
Data Science Prerequisites - Numpy, Matplotlib, and Pandas in Python - PDF and CDF
In this video, you will learn how to calculate PDF and CDF under normal distribution. This clip is from the chapter "SciPy" of the series "Data Science Prerequisites - NumPy, Matplotlib, and Pandas in Python".In this section, we will...
Curated Video
Data Science Prerequisites - Numpy, Matplotlib, and Pandas in Python - Generating Data
In this video, we will discuss how to generate data. This clip is from the chapter "NumPy" of the series "Data Science Prerequisites - NumPy, Matplotlib, and Pandas in Python".In this section of the course, we will dive into the world of...
Curated Video
Identify Distribution of Data by Observing Bell Curves
Identify Distribution of Data by Observing Bell Curves identifies the distribution of data given by observing bell curves.
Curated Video
R Programming for Statistics and Data Science - Distributions
This video explains distributions. This clip is from the chapter "Hypothesis Testing" of the series "R Programming for Statistics and Data Science".This section explains hypothesis testing.
Curated Video
Julia for Data Science (Video 20)
Julia is an easy, fast, open source language that if written well performs nearly as well as low-level languages such as C and FORTRAN. Its design is a dance between specialization and abstraction, providing high machine performance...
APMonitor
Data Engineering Summary Statistics
Summary statistics give valuable insights as one of the first steps in data engineering after the data is gathered. Statistics help to assess data quality and diversity. Data discovery with statistics is a common first activity and there...
Curated Video
Julia for Data Science (Video 25)
Julia is an easy, fast, open source language that if written well performs nearly as well as low-level languages such as C and FORTRAN. Its design is a dance between specialization and abstraction, providing high machine performance...
APMonitor
Data Science 🐍 Statistical Analysis
Once data is read into Python, a first step is to analyze the data with summary statistics. This is especially true if the data set is large. Summary statistics include the count, mean, standard deviation, maximum, minimum, and quartile...
Curated Video
Comparing Treatments Using Resampling: Determining the Effectiveness of New Salt Substitute and Fertilizer
In this video, the teacher explains how researchers can determine if there is a difference between two treatments using a resampling strategy. They use examples of comparing salt substitutes and fertilizers to demonstrate the process. By...
Curated Video
Design a computer system using tree search and reinforcement learning algorithms : Creating a Bandit with 4 Arms Using Python and Numpy
From the section: The Multi-Armed Bandit. In this section, we will learn about the basics and look at one of the most foundational concepts in Reinforcement Learning – The Multi-Armed Bandit We construct a model of a MAB environment from...
Curated Video
Predictive Analytics with TensorFlow 11.2: Developing a Multiarmed Bandit's Predictive Model
One of the simplest RL problems is called n-armed bandits. The thing is there are n-many slot machines but each has different fixed payout probability. The goal is to maximize the profit by always choosing the machine with the best...
Curated Video
Finding Percentages in a Normal Distribution Using Z Scores and Tables
In this lesson, you will learn how to use Z scores and statistics tables to find the percentage of a population that falls within a certain interval. This method is particularly useful when dealing with values that are not exactly 1-2 or...
Curated Video
Predicting Population Percentages Using a Graphing Calculator
In this video, students learn how to predict population percentages using a graphing calculator. The lesson focuses on the normal model and its application to data sets. It also covers the use of the empirical rule and explores different...
Curated Video
Estimating Percentages using the Empirical Rule
This video explains how to estimate the percentage of adult American females between 5 feet and 5 feet 10 inches tall using the empirical rule. The empirical rule states that approximately 68% of the data falls within one standard...
Curated Video
Statistics for Data Science and Business Analysis - Understanding the central limit theorem
This video is about the central limit theorem - one of the most important statistical concepts. This clip is from the chapter "Inferential Statistics Fundamentals" of the series "Statistics for Data Science and Business Analysis".This...
Curated Video
Predicting Intervals and Population Percentages Using the Empirical Rule
This video explains how to use the Empirical Rule to predict intervals and population percentages in a normal distribution. It covers the concept of normal distributions, the characteristics of the Empirical Rule, and how to apply it to...
Curated Video
Multi-Paradigm Programming with Modern C++ - More Range Examples
Everything you can do with loops and algorithms; you can also do with ranges. Thanks to lazy evaluation of views, the code becomes more functional, and often more compact. • Returning ranges from functions • Creating a new range that...
Brian McLogan
Learn how to create a normal distribution curve given mean and standard deviation
👉 Learn how to find probability from a normal distribution curve. A set of data are said to be normally distributed if the set of data is symmetrical about the mean. The shape of a normal distribution curve is bell-shaped. The normal...
Packt
Create a computer vision system using decision tree algorithms to solve a real-world problem : Introduction to MatPlotLib
From the section: Python Crash Course [Optional]. In this section, we’ll continue diving into Python data structures with tuples and dictionaries, functions, Boolean Operations and Loops, and libraries like Pandas, MatPlotLib and Seaborn...
Brian McLogan
Learn how to find the geometric probability from a figure
Learn how to find the geometric probability of an event. Given a geometric figure, we can find the geometric probability of an event by taken the area of the part of the geometric figure satisfying the event divided by the area of the...
Curated Video
Predictive Analytics with TensorFlow 3.5: Getting Started with Tensorflow – Linear Regression and Beyond
In this example, we will take a closer look at TensorFlow's and TensorBoard's main concepts and try to do some basic operations to get you started. The model we want to implement simulates the linear regression. • Create data into 2D space
Catalyst University
Wilcoxon Rank Sum Test: Theory and Tutorial in Excel
Wilcoxon Rank Sum Test: Theory and Tutorial in Excel
TMW Media
Normal Probability Density
This program covers the important topic of the Normal Probability Density in Probability and Statistics. We begin by discussing what the Normal Density is and why it is important. Next, we solve several problems that involve the Normal...