ARIMA stands for Auto Regressive Integrated Moving Average. It’s a statistical library used for analyzing and forecasting time series data. Models created using ARIMA library are more flexible than other statistical models like simple linear regression. Here’s a closer look at the terms that make up this acronym:
Continue reading Implementing ARIMA using Statsmodels and Python
Data visualization is the art of transforming information into a visual context, such as a map or graph. Through your journey in analyzing and preparing your data, you’ll often need to visually present your findings using some type of chart to make sense of the facts, numbers, and measurements.
After all, a picture is worth a thousand words (or in our case, a chart). However, to get the best use of a chart representation, you need to make sure you chose the perfect chart type to communicate your purpose and intentions. Choosing the perfect chart type for your goal can save you a lot of time and effort in order to better explain your data.
Continue reading How to choose the best chart type to present your dataset
Our experience of the world is multimodal — we see objects, hear sounds, feel the texture, smell odors and taste flavors and then come up to a decision. Multimodal learning suggests that when a number of our senses — visual, auditory, kinesthetic — are being engaged in the processing of information, we understand and remember more. By combining these modes, learners can combine information from different sources.
In machine learning, a hyperparameter is a configuration variable that’s external to the model and whose value is not estimated from the data given.
Hyperparameters are an essential part of the process of estimating model parameters and are often defined by the practitioner.
When a machine learning algorithm is used for a specific problem, such as using a grid search or a random search algorithm, then you’re actually tuning the hyperparameters of the model to discover the values that result in the most accurate predictions.
Continue reading Introduction to Learning Rates in Machine Learning
Hand detection is a fundamental sub-task of object detection that has historically been hard to implement. But there have been many technological advancements in the field of machine learning and AI in recent years.
One of the core technologies widely used is TensorFlow, an end-to-end open-source platform for machine learning. It has a wide-ranging, flexible ecosystem of tools, libraries, and community resources. With the power of TensorFlow technology, researchers and developers can easily develop and deploy ML-powered applications.
Continue reading Introduction to hand detection in the browser with Handtrack.js and TensorFlow
Like many developers exploring the world of wearables, I’m an avid fan of apps that track your exercise. Companies like Strava & Runkeeper have paved the way for what we can do with motion and health data, creating new and unique experiences that attract millions of users. However, I was always frustrated that I could automatically track my runs, but I still had to enter each gym set by hand.
Continue reading Introduction to Apple WatchKit with Core Motion — Tracking Jumping Jacks
In this tutorial, we’ll cover how to convert a model in PyTorch to the ONNX format and then load it to Caffe2. We’ll then use Caffe2’s mobile exporter to execute it on mobile.
Continue reading Using ONNX to Transfer Machine Learning Models from PyTorch to Caffe2 and Mobile
Apple’s SwiftUI announcement during last year’s WWDC (2019) was a welcomed surprise for Apple devs. The framework embraces a more declarative and reactive approach to building user interfaces—a complete paradigm shift from interface builder and storyboards. In a way, SwiftUI brings the joys of Swift to UI-building, signaling a coming departure of Objective-C inspired systems.
SwiftUI 1.0 (unofficial versioning), though, proved to still be somewhat a prototype framework, showing signs of its infancy. There were:
Frontier Design’s Video Star is a freemium video editing and creation app with a rich, deep toolkit that allows users to become the stars of their own music videos. From transitions, to blur and color effects, to adding 3D objects and text, and beyond, Video Star has a seemingly endless trove of fun capabilities to explore.
Vertex animation is the keyframed animation of individual vertices of a mesh. It is very beneficial for very complicated motion like that of cloth, hair, or water. It uses a flex controller bone to move the model through a series of flexes — one for each frame.
Vertex animation is included in almost all video or computer-based games. To animate the character, one just needs to vary the sampled line based on the current time.
Continue reading Vertex Animation in Lens Studio for Snapchat Lenses
