2022-05-28
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How to interpret logistic regression coefficients?

15 mins read Logistic Regression is a fairly simple yet powerful Machine Learning model that can be applied to various use cases. It’s […]
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2022-05-28
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Understanding interaction effects in regression analysis

22 mins read In regression, an interaction effect exists when the effect of an independent variable on a dependent variable changes, depending on […]
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2022-05-26
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Understanding Ordinal and One-Hot Encodings for categorical features

21 mins read Machine learning models require all input and output variables to be numeric. This means that if your data contains categorical […]
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2022-05-26
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When should we drop the first one-hot encoded column?

10 mins read Many machine learning models demand that categorical features are converted to a format they can comprehend via a widely used […]
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2022-05-26
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Alternatives for One-Hot Encoding of Categorical Variables

6 mins read One-hot encoding, otherwise known as dummy variables, is a method of converting categorical variables into several binary columns, where a […]
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2022-05-26
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Common mistakes to avoid as a Machine Learning Engineer

5 mins read In machine learning, there are many ways to build a product or solution and each way assumes something different. Many […]
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2022-05-25
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What are skip connections in deep learning?

17 mins read Nowadays, there is an infinite number of applications that someone can do with Deep Learning. However, in order to understand […]
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2022-05-24
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A guide on Maximum likelihood and Bayesian inference for parameter estimation

28 mins read Introduction In this post, I’ll explain what the maximum likelihood and Bayesian inference methods for parameter estimation are and go […]
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2022-05-19
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Understanding the basics of Bayesian Inference with Python Code

10 mins read Why did someone have to invent the Bayesian Inference? In one sentence: to update the probability as we gather more data. The […]
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2022-05-11
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23 Useful but less used Pandas Functions

11 mins read Pandas is so vast and deep that it enables you to execute virtually any tabular manipulation you can think of. […]
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2022-05-08
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Encoding categorical features using the category_encoders package

11 mins read There are loads of different ways to convert categorical variables into numeric features so they can be used within machine […]
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2022-05-04
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Understand different feature scaling techniques with Python code

19 mins read In many machine learning algorithms, to bring all features in the same standing, we need to do scaling so that […]
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2022-04-27
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Understanding and interpreting Residuals Plot for linear regression

27 mins read Interpreting Residual Plots to Improve Your Regression When you run a regression, calculating and plotting residuals help you understand and improve your […]
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2022-04-24
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Implementing Transformers step-by-step in PyTorch from scratch

14 mins read Doing away with clunky for-loops, the transformer instead finds a way to allow whole sentences to simultaneously enter the network […]
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2022-04-10
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Understanding ROC and Precision-Recall curves

25 mins read It can be more flexible to predict probabilities of an observation belonging to each class in a classification problem rather […]
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2022-04-09
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Finding an optimized portfolio of machine learning models using Sklearn, LazyPredict, and Precise Packages

10 mins read In this post, I will provide an example of the use of the precise Python package (and PyPortfolioOpt) to create a diversified portfolio of […]
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2022-04-09
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Delving into GPT-2 and GPT-3 Language Models

32 mins read This year, we saw a dazzling application of machine learning. The OpenAI GPT-2 exhibited an impressive ability to write coherent and passionate […]
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2022-03-28
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A tutorial on data science project experimentation with Jupyter, Papermill, and MLflow

7 mins read Your company (e.g., an e-commerce platform across several countries) is starting a new project on fraud detection. You begin by […]
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2022-03-27
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Interpreting coefficients of Dummy Variables in a Linear Regression Model

5 mins read Linear regression is a method we can use to quantify the relationship between one or more predictor variables and a response variable. […]
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2022-03-26
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Styling Pandas dataframes using Styler

7 mins read What is styling and why care? The basic idea behind styling is that a user will want to modify the way […]
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