Last Updated on January 13, 2020Model evaluation involves using the available dataset to fit a model and estimate its performance…

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## NLP Tutorial: MultiLabel Classification Problem using Linear Models

NLP Tutorial: MultiLabel Classification Problem using Linear ModelsGeorgios DrakosBlockedUnblockFollowFollowingJun 16This article presents in details how to predict tags for posts from…

Continue Reading## Predicting Diabetes using Logistic Regression with TensorFlow.js

We have the data, let get familiar with it!ExplorationWhile tfjs-vis is nice and well integrated with TensorFlow. js, it lacks…

Continue Reading## A quick run-through of Holt-Winters, Seasonal ARIMA and FB Prophet

A quick run-through of Holt-Winters, Seasonal ARIMA and FB ProphetGregory FeltonBlockedUnblockFollowFollowingJun 27gianfelton/Comparing-Holt-Winters-SARIMA-and-FBProphetThis is a simple notebook comparing the output of Holt-Winters,…

Continue Reading## Singapore Flat Price Predictor

I will be running multiple experiments and do some comparison with the base model. I will cover that in the…

Continue Reading## Transfer learning with a small data set- “nanos gigantum humeris insidentes”

Before we try to answer this question, let’s do another experiment. This time we’ll retrain the entire network, no pre-trained…

Continue Reading## Data Science Poem

By Igor Korolev, DO, PhD, BrainformatikaData science is pretty cool, Its full of many useful tools. R, and Python, and…

Continue Reading## What’s next for mapping apps? On route journey planning.

Simply yes — we will look into the benefits of approximating the route first later. Direction — this is more complicated; however fortunately for…

Continue Reading## Learning from Imbalanced Data

Not really. We have a few techniques that help us overcome this imbalance. Custom Loss FunctionPartial AugmentationClustered EnsemblesLet us look…

Continue Reading## Anomaly Detection with Time Series Forecasting

Anomaly Detection with Time Series Forecastingadithya krishnanBlockedUnblockFollowFollowingMar 3Hi, this is a follow-up article on anomaly detection(Link to the previous article:…

Continue Reading## Predicting Ratings with Matrix Factorization Methods

Predicting Ratings with Matrix Factorization MethodsHéctor LiraBlockedUnblockFollowFollowingFeb 19TL;DRMatrix Factorization methods approximate a matrix of ratings, R, by the product of…

Continue Reading## Training AlexNet with tips and checks on how to train CNNs: Practical CNNs in PyTorch(1)

Training AlexNet with tips and checks on how to train CNNs: Practical CNNs in PyTorch(1)Kushajveer SinghBlockedUnblockFollowFollowingFeb 17Welcome to the first…

Continue Reading## Building NLP Classifiers Cheaply With Transfer Learning and Weak Supervision

Building NLP Classifiers Cheaply With Transfer Learning and Weak SupervisionAn Step-by-Step Guide for Building an Anti-Semitic Tweet ClassifierAbraham StarostaBlockedUnblockFollowFollowingFeb 15Text…

Continue Reading## Dog Breed Classification using CNNs

Dog Breed Classification using CNNsDeniz Doruk NuhogluBlockedUnblockFollowFollowingFeb 9In today’s post, I will be showing you how to be make an exceptionally…

Continue Reading## Predictive Modeling: Picking the Best Model

Predictive Modeling: Picking the Best ModelTesting out different types of models on the same dataKailey SmithBlockedUnblockFollowFollowingFeb 8Whether you are working on predicting…

Continue Reading## Support Vector Machine: MNIST Digit Classification with Python; Including my Hand Written Digits

Support Vector Machine: MNIST Digit Classification with Python; Including my Hand Written DigitsUnderstanding SVM Series : Part 3SaptashwaBlockedUnblockFollowFollowingJan 20Following the previous detailed discussions…

Continue Reading## How to Accelerate Learning of Deep Neural Networks With Batch Normalization

Batch normalization is a technique designed to automatically standardize the inputs to a layer in a deep learning neural network.…

Continue Reading## How to Fix Vanishing Gradients Using the Rectified Linear Activation Function

The vanishing gradients problem is one example of unstable behavior that you may encounter when training a deep neural network.…

Continue Reading## Mask R-CNN for Ship Detection & Segmentation

Mask R-CNN for Ship Detection & SegmentationGabriel GarzaBlockedUnblockFollowFollowingJan 7Model predicting mask segmentations and bounding boxes for ships in a satellite…

Continue Reading## How to Improve Deep Learning Model Robustness by Adding Noise

Try running the example a few times.In this case, we can see a marked increase in the performance of the…

Continue Reading## Simple intent recognition and question answering with DeepPavlov

The tf-idf logistic regression that learns to assign weights to the words outperforms the rest tf-idf based models.ConclusionIn this article,…

Continue Reading## Upgrade your Image Classifier with Balanced data

[6]PCA OutputFrom the PCA summary its clear that the first 25 principal components hold more than 80% of the data.PCA…

Continue Reading## Using 3D visualizations to tune hyperparameters in ML models

To perform it we have to divide the data in 3 subsets: a train set (used to train the model),…

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