This tutorial covers the entire ML process, from data ingestion, pre-processing, model training, hyper-parameter fitting, predicting and storing the model for later use.We will complete all these steps in less than 10 commands that are naturally c...
Today, large companies have large I+D budgets that allow them to experiment and be at the cutting edge of new technologies; always adopting the newest, trying to adapt it to their own needs, trying to find the hidden value in each of them. It is n...
As usual, we have given ourselves the task of interviewing the winners of the competition "Google Play Store Rating Prediction" that ended a few days ago, having as winner Edimer "Siderus" from Colombia and with a score of 0.698709403908066 and wh...
We will create a complete project trying to predict customer spending using linear regression with Python. In this exercise, we have some historical transaction data from 2010 and 2011. For each transaction, we have a customer identifier (Customer...
This is probably one of the biggest worries of those starting in the area of data science, learning/refreshing mathImage by DataSource.aiLet’s be honest, most people didn’t do very well in math in school, maybe not even in college, and this is ver...
Here you will find a study plan divided by semesters so that you can start on January 1stWe are ending 2020 and it is time to make plans for next year, and one of the most important plans and questions we must ask is what do we want to study?, wha...
An overview of Machine Learning Algorithms(Source)“Machine intelligence is the last invention that humanity will ever need to make.”— Nick Bostrom.If you could look back a couple of years ago at the state of AI and compare it with its current stat...
sourceThere are two types of supervised machine learning algorithms: Regression and classification. The former predicts continuous value outputs while the latter predicts discrete outputs. For instance, predicting the price of a house in dollars i...
A plethora of online courses and tools promise to democratize the field, but just learning a few basic skills does not a true data scientist makeEvery few years, some academic and professional field gets a lot of cachet in the popular imagination....
In this article, I will present the 22 questions in fundamental statistics that you may encounter during interviews.1, What is Hypothesis Testing?Hypothesis Testing is a method of statistical inference. Based on data collected from a survey or an ...
“How many data science projects have you completed so far?”The domain of Data Science brings with itself a variety of scientific tools, processes, algorithms, and knowledge extraction systems from structured and unstructured data alike, for identi...
Infographic vector created by stories — www.freepik.comIntroductionGetting my first data science job was hard.It’s especially hard to break into data science when companies typically require a Master’s degree and a minimum of 2–3 years of experien...
Learn how they made their machine learning models and what tools they used with this interview to the top 10 of the competition leaderboard. A few days ago we finished the data science competition called "Real Estate Price Forecast" in which 139 d...
Python is one of thetop programming languages for a diverse range of tasks and domains. Python’s user-friendliness, high-level nature, and the emphasis on simplicity and enhanced code readability make it a favorable choice for many developers arou...
IntroductionAs we inch further into the year, I have seen more and more postings for data science positions, especially on LinkedIn, and other similar job-posting sites. After an expected lull due to current events, companies have figured out thei...
CreditsPredictive models have become a trusted advisor to many businesses and for a good reason. These models can “foresee the future”, and there are many different methods available, meaning any industry can find one that fits their particular ch...
CreditsIntroductionModel optimization is one of the toughest challenges in the implementation of machine learning solutions. Entire branches of machine learning and deep learning theory have been dedicated to the optimization of models.Hyperparame...
So, regression… aside from other algorithms and statistical models, it is one more building block upon which Machine Learning successfully works. In its core, regression aims to find the relationship between variables and for Machine Learning it i...
Photo by erika m on UnsplashIntroductionIn statistics, measures of central tendency are a set of “middle” values representative of the data points. Central tendency describes the distribution of data focusing on the central location around which a...