We've talked a lot about modeling data and making inferences about it, but today we're going to look towards the future at how machine learning is being used to build models to predict future outcomes. We'll discuss three popular types...

This video will look at logistic regression in detail, mainly used for classification problems with one or multiple independent variables.

Build your own spam detector using NLP techniques to identify common words in spam emails.

Learn 10 essential math concepts for software engineering and technical interviews. Understand how programmers use mathematics in fields like AI, game dev, crypto, machine learning, and more.

In this continuation video, explore the recommended order of taking the lessons in this learning program and how they are designed to provide a cohesive learning experience. This video will help you plan your learning effectively and...

In this video, we will see the recommended order of taking the lessons offered in this learning program, the logical progression of the course, and the optimal order to take the courses to maximize our learning and understanding of the...

In this video, you will learn to write Python code from scratch for financial analysis with ChatGPT using pairs trading strategies. This video will cover fundamental coding concepts such as data types, variables, loops, conditional...

In this lab video, you will learn how to use the Vertex AI web console to create a custom machine learning model by training it with your own dataset.
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This clip is from the chapter "Vertex AI - Machine Learning Framework" of...

This is a lab video on deploying training code to App Engine.
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This clip is from the chapter "Data Science Models with Google App Engine" of the series "Data Science Model Deployments and Cloud Computing on GCP".This section...

This video demonstrates sequence-to-sequence stock candlestick forecast.
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This clip is from the chapter "Recurrent Neural Networks" of the series "Fundamentals in Neural Networks".This section explains NLP, we will start with...

This video demonstrates how to design a recurrent neural network or RNN.
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This clip is from the chapter "Recurrent Neural Networks" of the series "Fundamentals in Neural Networks".This section explains NLP, we will start with...

This video demonstrates transfer learning.
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This clip is from the chapter "Convolutional Neural Networks" of the series "Fundamentals in Neural Networks".This section explains convolutional neural networks where you will start...

This video demonstrates a deeper CNN, where you will build a much bigger number of trainable parameters.
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This clip is from the chapter "Convolutional Neural Networks" of the series "Fundamentals in Neural Networks".This...

This video demonstrates the architecture and how to carry out the code using TensorFlow in collab and building a convolutional neural network.
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This clip is from the chapter "Convolutional Neural Networks" of the series...

Bidirectional recurrent neural networks (BRNN) connect two hidden layers of opposite directions to the same output. BRNNs are especially useful when the context of the input is needed. For example, in handwriting recognition, the...

Long short-term memory (LSTM) is an artificial recurrent neural network (RNN) architecture used in the field of deep learning. LSTM networks are well-suited to classifying, processing, and making predictions based on time series data...

Gated recurrent units (GRUs) are a gating mechanism in recurrent neural networks. GRUs have been shown to exhibit better performance on certain smaller and less frequent datasets.
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This clip is from the chapter "Recurrent...

Backpropagation through time (BPTT) is a gradient-based technique for training certain types of recurrent neural networks. It can be used to train Elman networks. The algorithm was independently derived by numerous researchers.
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The forward propagation in an RNN makes a few assumptions: 1) We assume the hyperbolic tangent activation function for the hidden layer. 2) We assume that the output is discrete as if the RNN is used to predict words or...

NLP is a tool for structuring data in a way that AI systems can process that deals with language. NLP uses AI to 'read' through a document and extract key information.
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This clip is from the chapter "Recurrent Neural Networks"...

A Recurrent neural network is a type of artificial neural network commonly used in speech recognition and natural language processing. Recurrent neural networks recognize data's sequential characteristics and use patterns to predict...

This video explains recurrent neural networks and why we want to use RNN.
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This clip is from the chapter "Recurrent Neural Networks" of the series "Fundamentals in Neural Networks".This section explains NLP, we will start with...

This video demonstrates convolutional operations in 1-dimension.
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This clip is from the chapter "Convolutional Neural Networks" of the series "Fundamentals in Neural Networks".This section explains convolutional neural...

Deeper neural networks are more difficult to train. We present a residual learning framework to ease the training of networks that are substantially deeper than those used previously.
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This clip is from the chapter...