Machine Learning: Python Linear Regression Estimator Using Gradient Descent
Author(s): Benjamin Obi Tayo Ph.D. Originally published on Towards AI. Implementation Using Python Estimator In this article, we describe how a simple python estimator can be built to perform linear regression using the gradient descent method. Let’s assume we have a one-dimensional …
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Author(s): Roberto Iriondo Originally published on Towards AI. References: Top highlight December 19, 2018, by Roberto Iriondo — Updated May 5, 2020 Everyone despises CAPTCHAs (humans, since bots do not have emotions) — Those annoying images containing hard to read the text, …
The Machine Learning Process
Author(s): Benjamin Obi Tayo Ph.D. Originally published on Towards AI. The machine learning process includes 4 main stages: Illustrating the Machine Learning Process. Define your project goals. What do you want to find out? Do you have the data to analyze? This …
Combating Media Bias with AWS Amazon Comprehend
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Machine Learning: Dimensionality Reduction via Linear Discriminant Analysis
Author(s): Benjamin Obi Tayo Ph.D. Originally published on Towards AI. A machine learning algorithm (such as classification, clustering or regression) uses a training dataset to determine weight factors that can be applied to unseen data for predictive purposes. Before implementing a machine …
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Author(s): Jun Wang Originally published on Towards AI. Word Embedding and Language Modeling U+007C Towards AI How to Get Deterministic word2vec/doc2vec/paragraph Vectors OK, welcome to our Word Embedding Series. This post is the first story of the series. You may find this …
Machine Learning: Dimensionality Reduction via Principal Component Analysis
Author(s): Benjamin Obi Tayo Ph.D. Originally published on Towards AI. How does PCA work? In machine learning, a dataset containing features (predictors) and discrete class labels (for a classification problem such as logistic regression); or features and continuous outcomes (for a linear …
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