David AndresforMachine Learning Pillsmlpills.hashnode.dev·Feb 1, 2023We've moved to www.mlpills.devHello! We decided to move the blog to: https://mlpills.dev/ You can subscribe to our newsletter so you don't miss any articles and all the exclusive content we share there! We now also have a Spanish version of the blog! With all the articles manu...Discuss·10 likes·65 readsArtificial Intelligence
David AndresforMachine Learning Pillsmlpills.hashnode.dev·Jan 24, 2023Forecasting methods in Time SeriesWhen working with time series data, it is important to assess the quality of a model in a way that accurately reflects real-world situations. Generally, the simplified process of building a Machine Learning model is the following: Process and clean ...Discuss·1 like·148 readsTime Series ForecastingPython
David AndresforMachine Learning Pillsmlpills.hashnode.dev·Jan 18, 2023Convolutional Neural Networks IIThe activation layers and pooling layers of the Convolutional Neural Networks (CNN) will be introduced, following the first part of this series where the convolutional layers were explained. Activation Layers Normally, the feature maps are passed thr...Discuss·10 likes·65 readsPython
Emmanuel Obicodeprophet.hashnode.dev·Jan 16, 2023Tradeoffs to consider before selecting a CSS framework☄️🌚.Introduction Very recently, I've been exposed to multiple CSS frameworks and they're all generally good tools. But there is often some debate about which is best to use and I've never really decided on one because, at different points in time, I've t...Discuss·17 likes·95 reads4articles4weeks
Pablo Jiménez MateoforMachine Learning Pillsmlpills.hashnode.dev·Jan 4, 2023Setup a Python environment in LinuxTo start working on Machine Learning you need tools, and those tools need to be installed in an environment. Think of an environment as a kind of workshop, except instead of a hammer or a screwdriver, you have Python and Keras. We will go through how...Discuss·6 likes·117 readsGet ready for Data Science and Machine LearningPython
David AndresforMachine Learning Pillsmlpills.hashnode.dev·Dec 7, 2022ARCH / GARCH models for Time SeriesVolatility is a statistical measure of the dispersion of data or variance around its mean over a certain period of time. In finance, it refers to how much the price changes between periods. For example, if it is high, the price may increase or decrea...Discuss·3 likes·148 readsTime Series ForecastingData Science
David AndresforMachine Learning Pillsmlpills.hashnode.dev·Dec 2, 2022Seasonal ARIMATime series can be seasonal. What does this mean? It means that our data exhibits a season or cycle that regularly repeats, for example, weekly, monthly or annually. There is something important to note. The presence of a cycle structure does not mea...Discuss·1 like·95 readsTime Series ForecastingData Science
David AndresforMachine Learning Pillsmlpills.hashnode.dev·Nov 23, 2022Parameters selection in ARIMA modelsARIMA models are a simple but powerful way of modelling time series. We saw that in the previous part. An ARIMA(p,d,q) model is defined by three parameters: p : autoregressive order d : difference order q : moving average order What p, q and d p...Discuss·1 like·156 readsTime Series Forecastingtime series
Atharva Hingeatharvatwts.hashnode.dev·Nov 13, 2022Learn Frontend Development for free!There are so many courses and tutorials available on the internet, that you may get confused and not actually select the best one that suits your learning speed and grasping ability. Although I believe that your hard work and consistency are what mat...Discuss·113 reads2Articles1Week
David AndresforMachine Learning Pillsmlpills.hashnode.dev·Nov 11, 2022Introduction to ARIMA modelsA time series is a series of data points ordered in time. Time is often the independent variable and the objective is usually to make a forecast for the future. It has many applications, some of which are forecasting sales, stock prices, temperatures...Discuss·1 like·173 readsTime Series Forecastingtime series
