Taraqur Rahman

Published in The Biased Outliers

·Pinned

How Should I Feed my Gradient Descent?

Gradient Descent is always hungry for data. How should we feed the data to the gradient descent? There are three common ways to feed in data for Gradient Descent (GD): Batch, Stochastic, and Mini-Batch. Is there a best one? Why do machine learning practitioners lean towards Mini-Batch GD? We will…

Deep Learning

4 min read

Deep Learning

4 min read

Published in OWL Integrations

·Feb 9

What the Duck?

We have been talking a lot about Ducks lately. You might have figured out by now that we are not referring to the ones that are flocking into memes. We are talking about the ones that are used to create connectivity. What is a Duck? Ducks are IoT devices that seamlessly connect to each…

IoT

4 min read

IoT

4 min read

Published in The Biased Outliers

·Jan 16

Moving Beyond Linearity — ISLR Series Chapter 7

Linear Regression is a great and simple model especially adding in some regularizers. However one of the limitations of linear regression is that we are assuming that the relationship between the features and the target variables are close to linear. This is a big assumption and it is not always…

Machine Learning

4 min read

Moving Beyond Linearity — ISLR Series Chapter 7

Machine Learning

4 min read

Published in OWL Integrations

·Jun 30, 2022

What Does the Data Say About the ClusterDuck Protocol v3?

The ClusterDuck Protocol (CDP) has evolved to version 3 thanks to the support of our open source community. There are many new things in the ClusterDuck Protocol version 3. …

Lora

5 min read

What Does the Data Say About the ClusterDuck Protocol v3?

Lora

5 min read

Published in The Biased Outliers

·Dec 24, 2021

Predicting Annual Water Usage in Baltimore using ARIMA

Time Series Forecasting Walkthrough — This is a project walkthrough from the book Introduction to Time Series Forecasting with Python by Jason Brownlee. He does a great job introducing the basic topics in univariate time series and does a walkthrough at the end summarizing everything we learned. The Annual Water Usage in Baltimore dataset has…

Time Series Forecasting

5 min read

Predicting Annual Water Usage in Baltimore using ARIMA

Time Series Forecasting

5 min read

Published in The Biased Outliers

·Sep 16, 2021

Introduction to Time Series

Time series can be a bit difficult at first. There are new lingo that needs to be learned in addition to all the other statistical jargon. This blog explains the must-know words for time series so that we have a foundation to build on when diving deeper. …

Time Series Forecasting

4 min read

Time Series Forecasting

4 min read

Published in The Biased Outliers

·Jul 8, 2021

Linear Model Selection and Regularization — ISLR Series Chapter 6

In Chapter 3, we talked about Linear Regression: how we can assume the data fits a linear model and predict using that linear model. The linear model falls short when there are a lot of features. It is good practice to collect as many data points as possible but the…

Statistical Learning

4 min read

Linear Model Selection and Regularization — ISLR Series Chapter 6

Statistical Learning

4 min read

Published in The Biased Outliers

·May 6, 2021

Resampling Methods — ISLR Series: Chapter 5

Now that we learned some basic models, it is time to determine how well our model performs on new data that the model has not seen before (model assessment) and how to choose the right model (model selection). …

Statistical Learning

6 min read

Resampling Methods — ISLR Series: Chapter 5

Statistical Learning

6 min read

Published in The Biased Outliers

·Apr 17, 2021

Classification — ISLR Series: Chapter 4 — Part I

Last blog we talked about linear regression: given some data, predict a numerical response. Chapter 4 and this blog goes over the scenario when the response variable is a not a numerical value but a class. This type of machine learning is called classification. The example that ISLR uses is…

Machine Learning

6 min read

Classification — ISLR Series: Chapter 4 — Part I

Machine Learning

6 min read

Published in ClusterDuck Protocol

·Apr 5, 2021

Setting up a BMP180 with the ClusterDuck Protocol

BMP180 is a great way to start learning how to integrate sensors with DuckLinks. The BMP180 are these really small sensors that collect temperature and pressure. It requires three steps: Soldering the BMP180 to a board and Uploading the firmware, and Collecting the data.

Lora

3 min read

Setting up a BMP180 using the ClusterDuck Protocol

Lora

3 min read