Crash Course
Supervised Machine Learning - Crash Course Statistics
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...
Crash Course
Regression - Crash Course Statistics
Today we're going to introduce one of the most flexible statistical tools - the General Linear Model (or GLM). GLMs allow us to create many different models to help describe the world - you see them a lot in science, economics, and...
Curated Video
Deep Learning - Recurrent Neural Networks with TensorFlow - RNN for Time Series Prediction
In this video, we will do the same forecasting exercise that we did with an autoregressive liner model, but with a simple RNN instead. This clip is from the chapter "Recurrent Neural Networks (RNNs), Time Series, and Sequence Data" of...
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Deep Learning - Recurrent Neural Networks with TensorFlow - Forecasting
In this video, we will discuss about forecasting. This clip is from the chapter "Recurrent Neural Networks (RNNs), Time Series, and Sequence Data" of the series "Deep Learning - Recurrent Neural Networks with TensorFlow".In this section,...
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Deep Learning - Recurrent Neural Networks with TensorFlow - Sequence Data
In this video, you will learn about sequence data. This clip is from the chapter "Recurrent Neural Networks (RNNs), Time Series, and Sequence Data" of the series "Deep Learning - Recurrent Neural Networks with TensorFlow".In this...
Curated Video
Financial Analysis - Build a ChatGPT Pairs Trading Bot - What Order Should I Take Your Courses In? (Part 2)
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...
Curated Video
Financial Analysis - Build a ChatGPT Pairs Trading Bot - What Order Should I Take Your Courses In? (Part 1)
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...
Curated Video
Financial Analysis - Build a ChatGPT Pairs Trading Bot - How to Code Yourself (Part 1)
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...
Curated Video
Financial Analysis - Build a ChatGPT Pairs Trading Bot - How to Code Yourself (Part 2)
Continuing from the previous video, we will dive deeper into Python coding concepts. This video will cover more advanced topics such as error handling, data manipulation, data visualization, and using common Python libraries such as...
Curated Video
Fundamentals of Neural Networks - Lab 2 - Sequence to Sequence Stock Candlestick Forecast
This video demonstrates sequence-to-sequence stock candlestick forecast. This clip is from the chapter "Recurrent Neural Networks" of the series "Fundamentals in Neural Networks".This section explains NLP, we will start with recurrent...
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Fundamentals of Neural Networks - Lab 1 - RNN in Text Classification
This video demonstrates how to design a recurrent neural network or RNN. This clip is from the chapter "Recurrent Neural Networks" of the series "Fundamentals in Neural Networks".This section explains NLP, we will start with recurrent...
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Fundamentals of Neural Networks - Lab 4 - Transfer Learning
This video demonstrates transfer learning. 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 with image...
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Fundamentals of Neural Networks - Lab 3 - Deep CNN
This video demonstrates a deeper CNN, where you will build a much bigger number of trainable parameters. This clip is from the chapter "Convolutional Neural Networks" of the series "Fundamentals in Neural Networks".This section explains...
Curated Video
Fundamentals of Neural Networks - Lab 2 - Introduction to CNN
This video demonstrates the architecture and how to carry out the code using TensorFlow in collab and building a convolutional neural network. This clip is from the chapter "Convolutional Neural Networks" of the series "Fundamentals in...
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Fundamentals of Neural Networks - Lab 4 - Functional API
This video demonstrates functional API versus sequential API. This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This section explains artificial neural networks where you will...
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Fundamentals of Neural Networks - Lab 3 - Introduction to Neural Network
This video demonstrates how to use Keras TensorFlow as API to essentially design and craft the neural network architecture. This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This...
Curated Video
Fundamentals of Neural Networks - Lab 2 - Introduction to TensorFlow — Remove the Throat-Clearing Sound in the Start of the Video
This video demonstrates some basic operations in TensorFlow such as objects and we will apply some mathematical operations to the Tensor objects. This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in...
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Fundamentals of Neural Networks - Lab 1 - Introduction to Python
This video demonstrates some of the basic commands in Python specifically the print statement, data structures, variables, and how to define a function. This clip is from the chapter "Artificial Neural Networks" of the series...
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Fundamentals of Neural Networks - Bi-Directional RNN
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...
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Fundamentals of Neural Networks - Long Short-Term Memory (LSTM)
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...
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Fundamentals of Neural Networks - Gated Recurrent Unit (GRU)
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. This clip is from the chapter "Recurrent Neural Networks"...
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Fundamentals of Neural Networks - Backward Propagation Through Time
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. This clip...
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Fundamentals of Neural Networks - Forward Propagation in RNN
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 characters. This...
Curated Video
Fundamentals of Neural Networks - Language Processing
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. This clip is from the chapter "Recurrent Neural Networks" of the...