Published in MLearning.ai·Oct 30, 2022Member-onlyDetailed answers that will help you ace your Data Science interviewI am starting a series on answering data science questions that you might be asked in an interview. These questions are ones that I have faced myself or have asked when I have been part of the interview team. The series should help you understand some of the technical questions…Machine Learning7 min readMachine Learning7 min read
Published in Patrick’s notes·May 8, 2022The essentials that Data Scientists need to know about web scrapingThe internet represents one of the most significant resources for data available for a practicing data scientist. The good news is that this data can be captured using a number of tools available in Python that can be learned rapidly. …Web Scraping6 min readWeb Scraping6 min read
Published in Patrick’s notes·Jan 21, 2022Predicting the sentiment of a tweet using NLP and Classification techniquesWhile Twitter has a love-hate relationship for many people, what we can all agree on is it represents one of the best sources for understanding public opinions and sentiment. Therefore. it’s no surprise to see growing levels of academic research using data obtained from the platform with various natural language…Data Science9 min readData Science9 min read
Published in Patrick’s notes·Jan 8, 2022Linear algebra for machine learning — part 1You need to learn linear algebra to truly understand the wonderful world of machine learning. This is part 1 of a number of articles on the subject exploring the linear algebra concepts that are most relevant to machine learning and data science. …Linear Algebra6 min readLinear Algebra6 min read
Published in Patrick’s notes·Jan 2, 2022Understanding autoencodersAutoencoders are an unsupervised learning technique used across a range of real-life applications such as dimensionality reduction, feature extraction and outlier detection. In terms of prerequisites, while this article is not particularly technical, it does require a sound understanding of neural networks. So, what are autoencoders?Machine Learning5 min readMachine Learning5 min read
Published in MLearning.ai·Dec 23, 2021As a data scientist you need to understand media mix modellingThere are an ever-increasing number of media channels that can be tapped into to increase a company’s customer base. Despite the benefit, advertising budgets for a company of any scale are finite and therefore it is imperative to understand how effective these marketing channels are and how a company can…Marketing6 min readMarketing6 min read
Published in MLearning.ai·Dec 4, 2021What data scientists keep missing about imbalanced datasetsMany data scientists fail to fully understand the problems imbalanced datasets cause and the methods to alleviate this. As data scientists we come across many different datasets where there is a clear dominance in some types of data instances (known as majority classes) with other types significantly underrepresented (minority classes)…Data Science5 min readData Science5 min read
Oct 30, 2021Understanding support vector machines: part 1 of 3Support vector machines are one of the most effective algorithms in solving classification tasks. By the end of this first article, I hope that you will be able to understand an overview of what support vector machines aims to achieve and giving you our problem for the “hard” case of…Machine Learning3 min readMachine Learning3 min read
Published in MLearning.ai·Oct 10, 2021Data Science fundamentals: explaining the bias-variance trade-offAs a data scientist, your aim when building a suitable model is to optimise the prediction of a target variable based on a number of indicators (features). So, how do we judge this optimisation? In machine learning, the goal is to estimate a function that minimizes the mean squared error…Data Science3 min readData Science3 min read
Sep 19, 2021Understanding decision trees (CART)When starting your knowledge journey in data science, one of the first techniques to master are decision trees. This is a classification-based technique where we train a model to classify new data points based on its most likely output. …Artificial Intelligence4 min readArtificial Intelligence4 min read
