+
Instructional Video5:35
Professor Dave Explains

Accuracy and Precision for Data Collection

12th - Higher Ed
In science, we love data! But what are the rules of data collection? How accurate and how precise can we get with our data? What do these words even mean? Let's find out!
+
Instructional Video3:47
Curated Video

Calculating Reliability, Accuracy & Precision

12th - Higher Ed
Ever wondered what the terms 'reliability', 'accuracy' and 'precision' really meant? On first glance they may appear to be the same, but this video explains what distinguishes them and how we can calculate each of them.
+
Instructional Video9:28
Packt

Practical Data Science using Python - Optimizing Classification Metrics

Higher Ed
This video explains optimizing classification metrics. This clip is from the chapter "Machine Learning" of the series "Practical Data Science Using Python".This section explains machine learning.
+
Instructional Video14:04
Curated Video

Practical Data Science using Python - Logistic Regression - Model Optimization 2

Higher Ed
This video demonstrates how to predict the level by taking 0.3 as the optimum threshold. This clip is from the chapter "Logistic Regression" of the series "Practical Data Science Using Python".This section explains logistic regression.
+
Instructional Video7:57
Curated Video

Precision and Safety: The Role of High-Tech Machines in Product Inspection

6th - Higher Ed
Take a behind-the-scenes look at how high-precision machines play a crucial role in ensuring the quality and safety of the products we buy every day. From using smart scales that guarantee exact weights to advanced X-rays that spot...
+
Instructional Video5:13
Packt

Evaluate a machine learning model : Better Measures than Accuracy

Higher Ed
From the section: Improving Model Accuracy. We start with reviewing previous day’s assignment by looking at an ideal solution and results. This module takes a pause from introducing any new model and focuses on improving the models and...
+
Instructional Video8:15
Curated Video

Data Science and Machine Learning (Theory and Projects) A to Z - Machine Learning Model Performance Metrics: The Confusion Matrix

Higher Ed
In this video, we will cover the confusion matrix. This clip is from the chapter "Machine Learning: Machine Learning Crash Course" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this section, we will...
+
Instructional Video10:12
Bozeman Science

Practice 3 - Planning and Carrying Out Investigations

12th - Higher Ed
Paul Andersen explains how investigations are used by scientists to answer questions and by engineers to test designs. He delineates be investigative and observational science. He demonstrates the formation of a good question the design...
+
Instructional Video8:42
Packt

Predictive Analytics with TensorFlow 8.4: CNN-based Predictive Model for Sentiment Analysis

Higher Ed
This video will try to see if we can use CNN for such a use case and experience much better accuracy. Well, the motivation here is that we know CNN is mostly suitable for handling image recognition, classification, or pattern...
+
Instructional Video12:20
Curated Video

Confidence Intervals - Crash Course Statistics

12th - Higher Ed
Today we’re going to talk about confidence intervals. Confidence intervals allow us to quantify our uncertainty, by allowing us to define a range of values for our predictions and assigning a likelihood that something falls within that...
+
Instructional Video11:42
Schooling Online

Chemistry Skills: Reliability Part 1

3rd - Higher Ed
A new contender joins the archery contest... Will he be a match for Robin Hood? Only time (and repeated trials) will tell! This lesson will explore the concept of reliability, including the subtle difference between accuracy and...
+
Instructional Video11:38
Schooling Online

Physics Skills: Reliability Part 1

3rd - Higher Ed
A new contender joins the archery contest... Will they be a match for Robin Hood? Only time (and repeated trials) will tell! This lesson will explore the concept of reliability, including the subtle difference between accuracy and...
+
Instructional Video11:52
Schooling Online

IB Physics Skills: Reliability Part 1

3rd - Higher Ed
A new contender joins the archery contest... Will they be a match for Robin Hood? Only time (and repeated trials) will tell! This lesson will explore the concept of reliability, including the subtle difference between accuracy and...
+
Instructional Video12:00
Schooling Online

IB Chemistry: Reliability Part 1

3rd - Higher Ed
A new contender joins the archery contest... Will they be a match for Robin Hood? Only time (and repeated trials) will tell! This lesson will explore the concept of reliability, including the subtle difference between accuracy and...
+
Instructional Video1:11
Curated Video

Rising Waters: A Warmer World

3rd - 11th
Earth’s global sea levels are rising – and are doing so at an accelerating rate. Waters in the ocean are expanding as they absorb massive amounts of heat trapped by greenhouse gases in Earth’s atmosphere. Glaciers and ice sheets are...
+
Instructional Video11:19
Bozeman Science

Significant Digits

12th - Higher Ed
Mr. Andersen explains significant digits and shows you how to use them in calculations.
+
Instructional Video10:39
Bozeman Science

The Scientific Method

12th - Higher Ed
Mr. Andersen gives a brief description of the scientific method.
+
Instructional Video3:44
Curated Video

88-South Antarctic Traverse: Year Two

3rd - 11th
For the second straight year, NASA researchers (Kelly Brunt and Adam Greeley) endured low temperatures, biting winds, and high altitude to conduct another 88-South Traverse. The 470-mile expedition in one of the most barren landscapes on...
+
Instructional Video5:18
Packt

Evaluate a machine learning model : Review of Classifying Images Using Support Vector Machines

Higher Ed
From the section: Improving Model Accuracy. We start with reviewing previous day’s assignment by looking at an ideal solution and results. This module takes a pause from introducing any new model and focuses on improving the models and...
+
Instructional Video1:51
Curated Video

Evaluate a machine learning model : Assignment – Getting Better Test Sample Results by Measuring Model Performance

Higher Ed
From the section: Improving Model Accuracy. We start with reviewing previous day’s assignment by looking at an ideal solution and results. This module takes a pause from introducing any new model and focuses on improving the models and...
+
Instructional Video2:45
Curated Video

Evaluate a machine learning model : Understanding the Results

Higher Ed
From the section: Improving Model Accuracy. We start with reviewing previous day’s assignment by looking at an ideal solution and results. This module takes a pause from introducing any new model and focuses on improving the models and...
+
Instructional Video2:57
Packt

Evaluate a machine learning model : Improving the Models

Higher Ed
From the section: Improving Model Accuracy. We start with reviewing previous day’s assignment by looking at an ideal solution and results. This module takes a pause from introducing any new model and focuses on improving the models and...
+
Instructional Video3:06
Packt

Evaluate a machine learning model : Model Evaluation

Higher Ed
From the section: Improving Model Accuracy. We start with reviewing previous day’s assignment by looking at an ideal solution and results. This module takes a pause from introducing any new model and focuses on improving the models and...
+
Instructional Video4:20
Professor Dave Explains

Calculating Percent Error

12th - Higher Ed
Sometimes we take measurements, and sometimes we're off by a little bit. How far off? Does it make sense to just use a number? Shouldn't we use something that tells us how far off we are relative to the true value? Yes we should, hence,...