Jun 21, 2022A Comparison of G7 Countries House Price MovementPython, FRED, Economic Data, Housing Price — Federal Reserve Economic Data (FRED) is an online database maintained by the Federal Reserve Bank of St. Louis that provides over 800,000 economic data series from more than 100 public and proprietary sources. With FRED API key, you can use any programming language that can parse XML or JSON to…Fred3 min readFred3 min read
Jan 16, 2022Building A Recommender System With Implicit Feedback Datasets Using Alternating Least SquaresRecSys, ALS, Collaborative Filtering — In real-world scenarios most feedback is not explicit but implicit. Implicit feedback is tracked automatically, like monitoring clicks, view times, purchases, etc. Thus it is much easier to collect. Think of yourself, how often you give a rating after purchasing a product vs. how often you click or purchase a…Python5 min readPython5 min read
Nov 22, 2021Fake News Classification with LSTM or Logistic RegressionTensorflow, Keras, DataSpell, Scikit-Learn, PyCharm — Fake news has become a focal point of discussion in the media over the past several years. Therefore, there is a need for an automated way to classify fake and real news accurately. This post attempts to eliminate the spread of rumors and fake news and helps people to identify…Lstm6 min readLstm6 min read
Published in Towards Data Science·Sep 3, 2021The Analysis on American National Election Studies (ANES)Statistics, survey, vote intention, public opinion, Joe Biden, Donald Trump — Recently, I have been very interested in analyzing data for political science research. Fortunately, its easy to find political science data, encyclopedias, and information about quantitative and qualitative research methods. The Data The ANES collects high quality, non-partisan survey data on voting and public opinion.Election 20209 min readElection 20209 min read
Published in Towards Data Science·Jul 18, 2021Forecasting the 2020 US Election Using Multilevel Regression with Post-stratificationPresidential election, Trump, Political Polls, PYMC3, Python — How to Estimate Public Opinion in the States The most commonly used method for estimating state- level opinion is called disaggregation. The process is simple and easy to implement: After combining a set of national polls, you calculate the opinion percentages disaggregated by state. The problem with disaggregation is that it requires a large number of national surveys…Bayesian Statistics8 min readBayesian Statistics8 min read
Published in Towards Data Science·Dec 23, 2020A Quick Introduction On Granger Causality Testing For Time Series AnalysisAugmented Dickey-Fuller (ADF) test, Kwiatkowski–Phillips–Schmidt–Shin (KPSS) tests, Vector Autoregressions (VA), Durbin–Watson statistic, Cointegration test — The Granger causality test is a statistical hypothesis test for determining whether one time series is a factor and offer useful information in forecasting another time series. For example, given a question: Could we use today’s Apple’s stock price to predict tomorrow’s Tesla’s stock price? If this is true, our…Time Series Analysis5 min readTime Series Analysis5 min read
Published in Towards Data Science·Nov 30, 2020A Bayesian Model for Estimating the Effects of Covid-19 VaccinesPYMC3, Bernoulli Distribution, Pfizer, Moderna, AstraZeneca — Because of the trials are still ongoing, researchers caution against making head-to-head comparisons of vaccines based on incomplete data. But for the sake of learning, we will do it anyway, just not making any meaningful conclusions. Recently, the announcements went out that the potential effectiveness of SARS-CoV-2 vaccine candidates developed…Bayesian Statistics4 min readBayesian Statistics4 min read
Published in Towards Data Science·Sep 8, 2020Time Series of Price Anomaly Detection with LSTMJohnson and Johnson, JNJ, Keras, Autoencoder, Tensorflow — Autoencoders are an unsupervised learning technique, although they are trained using supervised learning methods. The goal is to minimize reconstruction error based on a loss function, such as the mean squared error. In this post, we will try to detect anomalies in the Johnson & Johnson’s historical stock price time…Time Series Analysis4 min readTime Series Analysis4 min read
Published in Towards Data Science·Aug 2, 2020Multi Class Text Classification With Deep Learning Using BERTNatural Language Processing, NLP, Hugging Face — Most of the researchers submit their research papers to academic conference because its a faster way of making the results available. Finding and selecting a suitable conference has always been challenging especially for young researchers. However, based on the previous conferences proceeding data, the researchers can increase their chances of…NLP4 min readNLP4 min read
Published in Towards Data Science·Jul 22, 2020COVID Fake News Detection with a Very Simple Logistic RegressionNatural Language Processing, NLP, Scikit Learn — This time, we are going to create a simple logistic regression model to classify COVID news to either true or fake, using the data I collected a while ago. The process is surprisingly simple and easy. We will clean and pre-process the text data, perform feature extraction using NLTK library…NLP3 min readNLP3 min read
