t-SNE | T-distributed stochastic neighbor embedding The goal is to take a set of points in a high-dimensional space and find a faithful representation of those points in a lower-dimensional space, typically the 2D plane. The algorithm is non-linear and
A lot of Machine Learning problems consist of hundreds to thousands of features. Having such a large number of features poses certain problems. This problem is also sometimes known as The Curse of Dimensionality and Dimensionality Reduction or Dimension reduction
Introduction Visualization as a tool takes part of the analysis coming from the data scientist in order to extract conclusions from a dataset. In today’s article we are going to go through Matplotlib library. Matplotlib is a third-party library for
Introduction NumPy is a third-party library for numerical computing, optimized for working with single- and multi-dimensional arrays. Its primary type is the array type called ndarray. This library contains many routines for statistical analysis. Creating, Getting Info, Selecting and Util
Introduction We begin with the fourth and final article of our saga of training with Pandas. In this article we are going to make a summary of the different functions that are used in Pandas to perform the missing data
Introduction We begin with the third post of our data science training saga with Pandas. In this article we are going to make a summary of the different functions that are used in Pandas to perform Iteration, Maps, Grouping and
Introduction We begin with the second post of our training saga with Pandas. In this article we are going to make a summary of the different functions that are used in Pandas to perform Indexing, Selection and Filtering. Indexing, Selecting
We are continuing with our interview series (previously we had interviewed Diego Ojeda – Android Lead at Apiumhub, Serhii Zabolennyi – QA Automation engineer at Apiumhub, Javier Gomez – backend developer at Apiumhub, Cuong Le – Backend developer at Apiumhub & Oriol Saludes –
Introduction Today we will like to introduce one of the first inner training chapters in which we introduce the fundamentals of DataScience treatment tools. We are talking about Pandas, Numpy and Matplotlib. Pandas is a third-party library for numerical computing
