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Fishing for Insight
Author(s): Kal Lemma Originally published on Towards AI. School of Fish Collective Behavior can be seen all around us. What really defines collective behavior models is that there is no global orchestrator that directs any power, but rather many individual agents locally …
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 …
What is K-Fold Cross Validation?
Author(s): Saikat Biswas Originally published on Towards AI. Image Source: Unsplash K-Fold Cross Validation U+007C Towards AI Importance of K-Fold Cross Validation in Machine Learning One of the most important steps before feeding the data to our model Right before we proceed …
Step 4: Logistic regression
Author(s): Rashmi Margani Originally published on Towards AI. Blending NB And SVM U+007C Towards AI Naive Bayes(NB)-Support Vector Machine(SVM): Art Of State Result Hands-On Guide using Fast.ai SVM with NB feature: State of art performance model variance Before getting into Model variant …
Understanding The simple Mathematics Behind Simple Linear Regression
Author(s): Lawrence Alaso Krukrubo Originally published on Towards AI. How to verify if a Linear Relationship exists between two variables. Not a lot of people like Maths and for good reasons. I’m not exactly fond of it, but I try to keep …
Mumbai vs. Delhi, What is Your Choice? Let the Data Decide!
Author(s): Sreelatha S Originally published on Towards AI. Data Science Storytelling for comparing two cities U+007C Towards AI Data analysis of various factors for two cities like food, venues to visit, etc Photo by Parth Vyas on Unsplash Mumbai and Delhi are …
Attention Please: Document Classification
Author(s): Jon-Ross Presta Originally published on Towards AI. Top highlight The current state of Deep Learning practices is fascinating to me because there are interesting likenesses between the way that we humans process images and text, and the algorithms we employ to …
Outlier Detection and Treatment: A Beginner's Guide
Author(s): Swetha Lakshmanan Originally published on Towards AI. Nature of Outliers: Top highlight One of the most important steps in data pre-processing is outlier detection and treatment. Machine learning algorithms are very sensitive to the range and distribution of data points. Data …
How Regularization Helps in Data Overfitting
Author(s): Saikat Biswas Originally published on Towards AI. Top highlight Source: Unsplash Surely helps in reducing the pain of lookout for a perfect model “Knowledge is the treasure and practice is the key to it” Let me start this article with a …
What is SVM?
Author(s): Dhilip Subramanian Originally published on Towards AI. Top highlight Machine Learning Support Vector Machine (SVM): A Simple Visual Explanation — Part 1 SVM is a supervised classification method that separates data using hyperplanes. SVM is a supervised machine learning algorithm is …
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 …
The Covariance and Correlation Clutter…
Author(s): Astha Puri Originally published on Towards AI. For the longest time, I remember being confused between these two devils — covariance and correlation. And the resemblance DID NOT help! 🙁 So here I am, writing my first post and making an …
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 …
Billions of Rows, Milliseconds of Time- PySpark Starter Guide
Author(s): Ravi Shankar Originally published on Towards AI. Programming Intended Audience: Data Scientists with a working knowledge of Python, SQL, and Linux How often we see the below error followed by a terminal shutdown followed by despair over lost work: Memory Error- …
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