Machine Learning Pandas-Profiling: A useful EDA tool When loading a new data set, the first thing we do is to get an understanding of the data. This includes steps like determining the number of unique values, identifying the data type,
Machine Learning Linear Models Decoded - Part 1 In this article, I will present the linear models in terms of questions and answers that can be asked during an interview process. I will try to start from very basic interview questions
Interview Coding Problems Interview Coding Problems: 1.Two Sum 2.Longest Common Prefix 3.Longest Substring Without Repeating Characters A great way to improve your coding skills is by solving coding challenges. Solving different types of challenges and puzzles can help you become a better problem solver, learn the intricacies of a
Python Tricks How to "best" print out a list/tuple in Python For long enough I have used to print out a python list as below:a = [1,2,3] print(a)Which is kind of working but without printing it in a nice format.
Python Tricks “is” vs “==” for Object Comparisons In this article, I will discuss the difference between the "==" and the "is" operators. Photo by Aleks Dorohovich / UnsplashThe "==" operator compares by checking for equality while the "is" operator, compares identities. The two
Machine Learning Tmux an essential tool for Data Scientists Many data scientists get stuck with the manifold of tools available to them. In this article, I will present the Tmux tool. What it does best is turn a single terminal into a
NLP All you need to know about Regular expressions-Regex + Python code snippet to build your own tokenizer In this article, a useful tool in the NLP toolkit named regex will be presented in details.Regex is used as a metalanguage to find string patterns in blocks of textRegular expressions (regex
NLP What is an N-gram Multichannel Convolutional Neural Network for Text Classification Deep neural networks have achieved remarkable results in some NLP tasks, one of them is text classification, i.e., assigning a set of pre-defined tags on a text based on its content. Their
Machine Learning Importance of Cross-Validation Validation is probably in one of most important techniques that a data scientist use as there is always a need to validate the stability of the machine learning model-how well it would generalize
NLP Sentiment Analysis on IMDB movie dataset - Achieve state of the art result using a simple Neural Network In my previous articles, I used two models to predict whether the movie reviews were positive or negative using the IMDB dataset. If you haven't read those articles I would urge you to
NLP What is an Embedding Layer? A couple of months ago I had myself the same question, so I thought of writing an article trying to summarize and documented my understanding of an embedding layer.Table of ContentsImportanceDetailed ExplanationExampleWord2Vec
NLP Sentiment Analysis on IMDB movie dataset - Achieve state of the art result using Logistic Regression In my previous article, I used the Naive Bayes model to predict whether the movie reviews were positive or negative using the IMDB dataset. If you haven't read this article I would urge
Machine Learning Support Vector Machine vs Logistic Regression Support Vector Machine (SVM) is an algorithm used for classification problems similar to Logistic Regression (LR). LR and SVM with linear Kernel generally perform comparably in practice. The goal of this article is
NLP Sentiment Analysis on IMDB movie dataset - Achieve state of the art result using Naive Bayes NLP refers to any kind of modelling where we are working with natural language text. Sentiment Analysis is a one of the most common NLP task that Data Scientists need to perform. Interestingly
NLP NLP Tutorial: Topic Modeling with Singular Value Decomposition (SVD) and Truncated SVD (fbpca and Sklearn python libraries used) Topic modeling is an interesting task for someone to start getting familiar with NLP. Briefly, it is the task of using unsupervised learning to extract the main topics (represented as a set of
NLP NLP Tutorial: MultiLabel Classification Problem using Linear Models This article presents in details how to predict tags for posts from StackOverflow using Linear Model after carefully preprocessing our text features.Table of ContentsIntroductionDatasetImport Libraries and Load the dataText PreprocessingEDATransforming text to
NLP Transforming tokens into useful features (BOW,TF-IDF) In my previous article, I presented different methods to preprocess text and extract useful tokens. However, these tokens are only useful if you can transform them into features for your machine learning model.
NLP All you need to know about NLP Text Preprocessing Text preprocessing is a severely overlooked topic and a lot NLP applications fail badly due to use of wrong kind of text preprocessing.With that in mind, I thought of writing an article
Interview Coding Problems How to nail a Data Scientist SQL interview (includes SQL code snippets to tough interview questions) - Part 2 As we already know Data Science/Machine Learning is such a multi-disciplinary field means that the sheer volume of material you need to feel properly prepared can become overwhelming.The sure thing is
Machine Learning Random Forest regression model Advanced Topics (+ Python code snippet using Sklearn) In my previous article, I presented the Random Forest Regressor model. If you haven't read this article I would urge you to read it before continuing. In simple terms, a Random forest is
Machine Learning Random Forest Regression model explained in depth In my previous article, I presented the Decision Tree Regressor algorithm. If you haven't read this article I would urge you to read it before continuing. The reason is that the Decision Tree
Interview Coding Problems How to nail a Data Scientist SQL interview (includes SQL code snippets to tough interview questions) - Part 1 As we already know Data Science/Machine Learning is such a multi-disciplinary field means that the sheer volume of material you need to feel properly prepared can become overwhelming.The sure thing is
Machine Learning Entity Embeddings of Categorical Variables in Neural Networks Categorical variables are known to hide and mask lots of interesting information in a data set and many times they might even be the most important variables in a model. A good data
Interview Coding Problems Interview Coding Problems: 1.Implement Trie (Prefix Tree) 2. Longest Substring with At Most K Distinct Characters 3. 3Sum A great way to improve your coding skills is by solving coding challenges. Solving different types of challenges and puzzles can help you become a better problem solver, learn the intricacies of a
Interview Coding Problems Interview Coding Problems: 1. Count the number of unival subtrees of a binary tree 2.Find the largest sum of non-adjacent numbers of a list 3.Staircase Problem A great way to improve your coding skills is by solving coding challenges. Solving different types of challenges and puzzles can help you become a better problem solver, learn the intricacies of a
