2022-07-03
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Visual comparison of decision boundaries for different classifiers

33 mins read There are many debates on how to decide on the best classifier. Measuring the Performance Metrics score, and getting the […]
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2022-07-01
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Handling imbalanced datasets for machine learning tasks

12 mins read You can find the implementation of codes in this post in the GitHub Gist. Introduction When observation in one class […]
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2022-06-26
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A complete guide on Pandas Grouping, Aggregating, and Transformation

51 mins read Introduction One of the most basic analysis functions is grouping and aggregating data. In some cases, this level of analysis […]
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2022-06-25
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Understanding Moving Average Model in Time Series with Python

10 mins read One of the foundational models for time series forecasting is the moving average model, denoted as MA(q). This is one […]
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2022-06-23
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A tutorial on Pandas apply, applymap, map, and transform

16 mins read In Data Processing, it is often necessary to perform operations (such as statistical calculations, splitting, or substituting values) on a […]
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2022-06-23
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Understanding Self-Attention in Transformers with example

10 mins read What do BERT, RoBERTa, ALBERT, SpanBERT, DistilBERT, SesameBERT, SemBERT, SciBERT, BioBERT, MobileBERT, TinyBERT and CamemBERT all have in common? And […]
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2022-06-19
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Evaluation metrics for Multi-Label Classification with Python codes

10 mins read In a traditional classification problem formulation, classes are mutually exclusive. In other words, under the condition of mutual exclusivity, each […]
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2022-06-19
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Understanding Micro, Macro, and Weighted Averages for Scikit-Learn metrics in multi-class classification with example

11 mins read The F1 score (aka F-measure) is a popular metric for evaluating the performance of a classification model. In the case […]
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2022-06-19
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Why are precision, recall, and F1 score equal when using micro averaging in a multi-class problem?

9 mins read In one of my projects, I was wondering why I get the exact same value for precision, recall, and the F1 score when using scikit-learn’s metrics. […]
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2022-06-14
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Deploying and sharing Machine Learning projects easily using Gradio

7 mins read Students or Professionals from other streams, like business studies, practice and excel in data science. But when it comes to […]
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2022-06-13
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Common loss functions for training deep neural networks with Keras examples

30 mins read Deep neural networks are trained using the stochastic gradient descent optimization algorithm. As part of the optimization algorithm, the error for […]
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2022-06-13
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Detecting elbow/knee points in a graph using Python

16 mins read Theory When working with data, it is sometimes important to know where a data point’s “relative costs to increase some […]
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2022-06-10
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Minimal PyTorch LSTM example for regression and classification tasks

10 mins read The Idea Behind RNNs Recurrent neural networks in general maintain state information about data previously passed through the network. This […]
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2022-06-06
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Understand Q-Learning in Reinforcement Learning with a numerical example and Python implementation

14 mins read This tutorial introduces the concept of Q-learning through a simple but comprehensive numerical example.  The example describes an agent which […]
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2022-06-03
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A complete guide on feature selection techniques with Python code

33 mins read Considering you are working on high-dimensional data that’s coming from IoT sensors or healthcare with hundreds to thousands of features, […]
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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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