From Developer to Time Series Forecaster in 7 Days. Python is one of the fastest-growing platforms for applied machine learning. In this mini-course, you will discover how you can get started, build accurate models and confidently complete predictive modeling time series forecasting projects using Python in 7 days. This is a big and important post. […]
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How to Train a Final Machine Learning Model
The machine learning model that we use to make predictions on new data is called the final model. There can be confusion in applied machine learning about how to train a final model. This error is seen with beginners to the field who ask questions such as: How do I predict with cross validation? Which […]
How to Get Started with Kaggle
4-Step Process for Getting Started and Getting Good at Competitive Machine Learning. Kaggle is a community and site for hosting machine learning competitions. Competitive machine learning can be a great way to develop and practice your skills, as well as demonstrate your capabilities. In this post, you will discover a simple 4-step process to get […]
Python Environment for Time Series Forecasting
The Python ecosystem is growing and may become the dominant platform for applied machine learning. The primary rationale for adopting Python for time series forecasting is because it is a general-purpose programming language that you can use both for R&D and in production. In this post, you will discover the Python ecosystem for time series […]
How to Create a Linux Virtual Machine For Machine Learning Development With Python 3
Linux is an excellent environment for machine learning development with Python. The tools can be installed quickly and easily and you can develop and run large models directly. In this tutorial, you will discover how to create and setup a Linux virtual machine for machine learning with Python. After completing this tutorial, you will know: […]
Time Series Forecasting With Python
Introduction to Time Series Forecasting With Python Discover How to Prepare Data and Develop Models to Predict the Future Time Series Problems are Important Time series forecasting is an important area of machine learning that is often neglected. It is important because there are so many prediction problems that involve a time component. These problems […]
How to Check if Time Series Data is Stationary with Python
Time series is different from more traditional classification and regression predictive modeling problems. The temporal structure adds an order to the observations. This imposed order means that important assumptions about the consistency of those observations needs to be handled specifically. For example, when modeling, there are assumptions that the summary statistics of observations are consistent. […]
Top Books on Time Series Forecasting With R
Time series forecasting is a difficult problem. Unlike classification and regression, time series data also adds a time dimension which imposes an ordering of observations. This turns rows into a sequence which requires careful and specific handling. In this post, you will discover the top books for time series analysis and forecasting in R. These […]
Machine Learning Algorithms From Scratch: With Python
Machine Learning Algorithms From Scratch Discover How to Code Machine Algorithms in Python (Without Libraries) You Learn Best By Implementing Algorithms From Scratch …But You Need Help With The First Step Developers Learn Best By Trying Things Out… If you’re like me, you don’t really understand something until you can implement it from scratch. You […]
How To Implement Logistic Regression From Scratch in Python
Logistic regression is the go-to linear classification algorithm for two-class problems. It is easy to implement, easy to understand and gets great results on a wide variety of problems, even when the expectations the method has of your data are violated. In this tutorial, you will discover how to implement logistic regression with stochastic gradient […]