Do Ray Bradbury, Arthur C. Clarke, Jules Verne, Philip K. Dick, Hugo Gernsback, Robert Heinlein, or Isaac Asimov hold a candle to H.G. Wells when it comes to correctly predicting the future of science via science fiction? And why does...

Today we’re going to talk about why many predictions fail - specifically we’ll take a look at the 2008 financial crisis, the 2016 U.S. presidential election, and earthquake prediction in general. From inaccurate or just too little data...

So now that we’ve built and programmed our very own CPU, we’re going to take a step back and look at how CPU speeds have rapidly increased from just a few cycles per second to gigahertz! Some of that improvement, of course, has come from...

Thanks to modern science and technology, we can predict what the weather will be like in 5 days, but it’s still a bit more challenging to predict what will happen to us and our societies.

Treo creator Jeff Hawkins urges us to take a new look at the brain -- to see it not as a fast processor, but as a memory system that stores and plays back experiences to help us predict, intelligently, what will happen next.

Miss Palomine explains that a scientist makes predictions based on observations, made either by himself or by other scientists. She defines both words and gives examples.

Tufts University philosopher Brian Epstein describes how his experiences as a management consultant giving completely incorrect predictions of many key features of the social world gave him a deep appreciation of how deceptively...

This video shows you how to create a Prophet model to predict where and how intense wildfires will be.

Explore how machine learning can predict who survived the Titanic's sinking in this beginner AI science project

Genome editing tool CRISPR helps reveal genetic regulation behind colors and patterns in butterfly wings



Description: Butterflies and moths constitute 10 percent of all known biodiversity in terms of numbers of...

Tornadoes claim hundreds of lives and cause billions of dollars in damages in the United States. With support from the National Science Foundation, computer scientist Amy McGovern at the University of Oklahoma is working to find answers...

In this lab video, you will learn how to serve a machine learning model using the Vertex AI Prediction service. You will use a pre-trained model and create an endpoint to make predictions on new data.
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This clip is from the...

This video explains logistic regression - model evaluation - AUC-ROC.<br<br/>/>

This clip is from the chapter "Logistic Regression" of the series "Practical Data Science Using Python".This section explains logistic regression.

Interpolation constructs new prediction points from a discrete set of known data points. There are many types of interpolation such as nearest neighbor (piecewise constant), linear, polynomial, cubic spline, and basis...

In this video, we will see working principles of predictive model. We will also see why to choose predictive analytics. We will also look at some linear algebra.<br/>
• Look at the working principle of predictive model

This video tutorial discusses outbreak prediction using AI and data science, focusing on the current COVID-19 pandemic. The tutorial covers topics such as exponential growth models, the SIR model, and the importance of flattening the...

In this video, we will see how we could develop several predictive models for Titanic survival prediction and do some analytics using them. In particular, we will discuss logistic regression, random forest, and linear SVM. We start with...

kNN is non-parametric and instance-based and is used in supervised learning. In this video, we will see working principles of kNN, we will also implement kNN-based predictive model. • See the working principles of kNN • Implement a...

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...

In this video, we will see how to perform a bit more complex predictive analytics using the bag-of-words concept of NLP with TensorFlow. At first, we will formalize the problem, and then will explore the dataset that will be used....

In this video, we will dive into coding and learn about the autoregressive linear model for time series prediction.
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This clip is from the chapter "Recurrent Neural Networks (RNNs), Time Series, and Sequence Data" of the...

In this video, we will discuss some widely used statistical concepts required in predictive analytics, followed by some basic understanding of predictive modeling, such as random sampling, central limit theorem, hypothesis testing...

This video explains predicting whether it will rain or not and testing the predictions.
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This clip is from the chapter "Machine Learning with Python" of the series "Python in Practice - 15 Projects to Master Python".This...

RNNs, specifically LSTM models, are often a difficult topic to understand. Time series prediction is a useful application for RNNs because of temporal dependencies in the data. Time series data is abundantly available online. In this...