Introduction Hey there! Just finished another deep learning project several hours ago, now I want to share what I actually…
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Collin Ching
How to program and debug more effectively as a data scientistLessons from my first data science…Logistic regression theory for practitionersKey intuition…
Continue ReadingTrain-Test Split for Evaluating Machine Learning Algorithms
The train-test split procedure is used to estimate the performance of machine learning algorithms when they are used to make…
Continue ReadingHow to Fix k-Fold Cross-Validation for Imbalanced Classification
Last Updated on January 13, 2020Model evaluation involves using the available dataset to fit a model and estimate its performance…
Continue ReadingNLP 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 ReadingPredicting 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 ReadingA 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 ReadingSingapore Flat Price Predictor
I will be running multiple experiments and do some comparison with the base model. I will cover that in the…
Continue ReadingTransfer 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 ReadingData Science Poem
By Igor Korolev, DO, PhD, BrainformatikaData science is pretty cool, Its full of many useful tools. R, and Python, and…
Continue ReadingWhat’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 ReadingLearning from Imbalanced Data
Not really. We have a few techniques that help us overcome this imbalance. Custom Loss FunctionPartial AugmentationClustered EnsemblesLet us look…
Continue ReadingAnomaly 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 ReadingPredicting 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 ReadingTraining 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 ReadingBuilding 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 ReadingDog 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 ReadingPredictive 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 ReadingSupport 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 ReadingHow 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 ReadingHow 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 ReadingMask 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 ReadingHow 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 ReadingSimple 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 ReadingUpgrade 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…
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