Analysis of the Learning Rate in Gradient Descent Algorithm Using Python
Author(s): Jalal Mansoori Originally published on Towards AI. In this tutorial, you’ll learn, implement, visualize the Performance of Gradient descent by trying different sets of learning rate values. Image by Author. Gradient Descent EquationWhat is Linear regression?What is Gradient Descent?Comparison between different …
Example 1: Extract a Table from PDF File Using Python
Author(s): Benjamin Obi Tayo Ph.D. Originally published on Towards AI. Demonstration of parsing PDF files using Python & R API Top highlight Data is key for any analysis in data science, be it inferential analysis, predictive analysis, or prescriptive analysis. The predictive …
Address Limitation of RNN in NLP Problems by Using Transformer-XL
Author(s): Edward Ma Originally published on Towards AI. Limitations of recurrent neural networks Photo by Joe Gardner on Unsplash Recurrent Neural Network (RNN) offers a way to learn a sequence of inputs. The drawback is that it is difficult to optimize due …
Unified Language Model Pre-training for Natural Language Understanding and Generation
Author(s): Edward Ma Originally published on Towards AI. Using UNILM to tackle natural language understanding (NLU) and natural language generation (NLG) Photo by Louis Hansel on Unsplash Recent state-of-the-art NLP pre-trained models also use a language model to learn contextualized text representation. …
Tutorial on Data Visualization: Weather Data
Author(s): Benjamin Obi Tayo Ph.D. Originally published on Towards AI. Weather data analysis and visualization using Python’s Matplotlib Data Visualization is more of an Art than Science. To produce a good visualization, you need to put several pieces of code together for …
50+ Python 3 Tips & Tricks
Author(s): Eyal Trabelsi Originally published on Towards AI. Programming, Python These Python Gems Will Make Your Code Beautiful and Elegant Here is a list of python tips and tricks to help you write an elegant Python 3 code! This article is divided …
Cross-lingual Language Model
Author(s): Edward Ma Originally published on Towards AI. Discussing XLMs and unsupervised cross-lingual word embedding by multilingual neural language models Photo by Edward Ma on Unsplash A pre-trained model is proven to improve the downstream problem. Lample and Conneau propose two new …
Building a Recommender System With Pandas
Author(s): Lawrence Alaso Krukrubo Originally published on Towards AI. Full Guide to Build a Recommender System U+007C Towards AI Hello World, in just a few minutes, I’d show you some pretty effective ways to use Pandas for Data Science. I assume you …
Bias-Variance Tradeoff Illustration Using Pylab
Author(s): Benjamin Obi Tayo Ph.D. Originally published on Towards AI. In statistics and machine learning, the bias-variance tradeoff is the property of a set of predictive models whereby models with a lower bias in parameter estimation have a higher variance of the …
Importance of Choosing the Correct Hyper-parameters While Defining a Model
Author(s): Saikat Biswas Originally published on Towards AI. Source: Unsplash Hyper-parameter Optimization U+007C Towards AI Often considered the trickiest part of optimizing a machine learning algorithm. Correct hyperparameter tuning can save a lot of time and help deploy the ML model faster …
An Introduction to Time-series Analysis Using Python and Pandas
Author(s): Oscar Arzamendia Originally published on Towards AI. Assumptions Very recently I had the opportunity to work on building a sales forecaster as a POC. It was a challenging project with a cool MVP as an outcome, and through this post, I …
A Gaussian Approach to the Detection of Anomalous Behavior in Server Computers
Author(s): Navoneel Chakrabarty Originally published on Towards AI. Let’s detect the anomaly… Anomaly Detection is a different variant of Machine Learning Problems that falls under Semi-Supervised Learning. It is Semi-Supervised because, in Anomaly Detection (also popularly known as Outlier Detection), models often …
Application of Synthetic Minority Over-sampling Technique (SMOTe) for Imbalanced Datasets
Author(s): Navoneel Chakrabarty Originally published on Towards AI. In Data Science, imbalanced datasets are no surprises. If the datasets intended for classification problems like Sentiment Analysis, Medical Imaging or other problems related to Discrete Predictive Analytics (for example-Flight Delay Prediction) have an …
Bad and Good Regression Analysis
Author(s): Benjamin Obi Tayo Ph.D. Originally published on Towards AI. Regression models are the most popular machine learning models. Regression models are used for predicting target variables on a continuous scale. Regression models find applications in almost every field of study, and …
Machine Learning: Python Linear Regression Estimator Using Gradient Descent
Author(s): Benjamin Obi Tayo Ph.D. Originally published on Towards AI. Implementation Using Python Estimator In this article, we describe how a simple python estimator can be built to perform linear regression using the gradient descent method. Let’s assume we have a one-dimensional …
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