NLP Learning Series (Part 2)Conventional Methods for Text ClassificationTeaching Machines to Learn TextRahul AgarwalBlockedUnblockFollowFollowingFeb 7This is the second post of the NLP…
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Don’t let them GO!
it appears that the paid/free status is not influencing termination of the account. On the other hand, active males are…
Continue ReadingPredicting “Bikeability” in U.S. Cities
After gathering and cleaning data from the aforementioned sources, I needed to join the disparate information. One main source of…
Continue ReadingDimensions and degrees of freedom
In this system we can’t, by design. So even if we collect the data of the 3 flows, it doesn’t…
Continue ReadingPeople Tracking using Deep Learning
People Tracking using Deep LearningDoing cool things with data!Priya DwivediBlockedUnblockFollowFollowingFeb 7IntroductionObject Tracking is an important domain in computer vision. It involves the…
Continue ReadingThe Best Note Taking/Task Manager App for Data Science Research Projects
The Best Note Taking/Task Manager App for Data Science Research ProjectsSterling Osborne, PhD ResearcherBlockedUnblockFollowFollowingFeb 13Notion at first appears like any other…
Continue ReadingFeature Selection with sklearn and Pandas
Feature Selection with sklearn and PandasIntroduction to Feature Selection methods and their implementation in PythonAbhini ShetyeBlockedUnblockFollowFollowingFeb 10Feature selection is one of the…
Continue ReadingNeural Networks seem to follow a puzzlingly simple strategy to classify images
Why should a ResNet-50 learn about complex large-scale relationships like object shape if the abundance of local image features is…
Continue ReadingPredicting House Prices using Machine Learning
One approach is to create an annotated heatmap. This will allow us to easily see how strongly is each variable…
Continue ReadingSupervised Learning: Basics of Classification and Main Algorithms
Supervised Learning: Basics of Classification and Main AlgorithmsVictor RomanBlockedUnblockFollowFollowingJan 31IntroductionAs stated in the first article of this series, Classification is…
Continue ReadingGetting Started with Recommender Systems and TensorRec
Getting Started with Recommender Systems and TensorRecPrototyping a recommender system, step-by-step. James KirkBlockedUnblockFollowFollowingJan 22Recommender systems are used in many products…
Continue ReadingCurse of Dimensionality
Curse of DimensionalityBadreesh ShettyBlockedUnblockFollowFollowingJan 15In Machine Learning, we often have high-dimensional data. If we’re recording 60 different metrics for each…
Continue ReadingInverting Discriminative Representations with HyperNets
Inverting Discriminative Representations with HyperNetsExploring the utility of HyperNets in overcoming traditional models’ limitations when inverting discriminative representations. Alexey PotapovBlockedUnblockFollowFollowingJan…
Continue ReadingOptimize Data Science Models with Feature Engineering
My name (“Pauline”) is old fashion without much room for abbreviation. I assumed the following list of features based on…
Continue ReadingAd Demand Forecast with Catboost & LightGBM
It is interesting to see that item_seq_number has the most significant impact on deal probability in lightGBM model, however, in…
Continue ReadingLet’s Find Donors For Charity With Machine Learning Models
It is a ratio of true positives(words classified as spam, and which are actually spam) to all the words that…
Continue ReadingA brief introduction to Slow Feature Analysis
This can be remedied by doing a non-linear expansion of the time series S first, then finding linear features of…
Continue ReadingFeature Selection Using Random forest
In random forests, the impurity decrease from each feature can be averaged across trees to determine the final importance of…
Continue ReadingIdentifying the Most Important Features for Student’s Educational Success
For this reason, Linear Regression (both with and without Lasso Regularization) were chosen since they are simple models that allow…
Continue ReadingExploratory Data Analysis, Feature Engineering and Modelling using Supermarket Sales Data. Part 1.
e.t.cYou get the hang of it.I could also create features from the existing ones by doing what we call Feature…
Continue ReadingA Gentle Customer Segmentation approach for mail-order Industries
This gives us a basis for dropping all the rows with more than 70% of NaN values, thereby obtaining a…
Continue ReadingPredicting number of Bike-share Users
Our goal is to use and optimize Machine Learning models that effectively predict the number of ride-sharing bikes that will…
Continue ReadingData Pre Processing Techniques You Should Know
Today we will be discussing feature engineering techniques that can help you to score a higher accuracy.As you know data…
Continue ReadingFit to Print: Finding the medium in the message
This tool can take a new article, find its best stylistic match and highlight some changes that might bring the…
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