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Sefik Ilkin Serengil

Code wins arguments

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Category: Machine Learning

How Modin Can Keep Data Scientists From Pandas

Data scientists tend to use pandas for data transformation because it is pretty. I witnessed many times that feature engineering … More

docker, feature engineering, modin, pandas, python

A Gentle Introduction to Auto-Keras

Finding the correct network structure and hyper-parameters is a totally black box in deep learning. There is no rule or … More

automl, emotion analysis, facial expression recognition, fer 2013

Tips and Tricks for GPU and Multiprocessing in TensorFlow

Having a GPU shows the wealth. Today, you should spend thousands of dollars to have a good one. For example, … More

gpu, multiprocessing, python, tensorflow

Machine Learning meets Blockchain

Solutions come after problems but exceptionally blockchain is a solution looking for its problems. We cannot find a completely solution … More

adversarial attacks, bitcoin, blockchain, crypto, paypal mafia

Machine Learning Wars: Deep Learning vs GBM

Machine learning studies have unfortunately bi-polarization. Practitioners mostly adopt either deep learning or gradient boosting machines. They might support these … More

deep learning, gbm, kaggle, KDDCup, superman

Apparent Age and Gender Prediction in Keras

Computer vision researchers of ETH Zurich University (Switzerland) announced a very successful apparent age and gender prediction models. They both … More

age prediction, deep learning, gender prediction, keras, python, vgg

Using Custom Activation Functions in Keras

Almost every day a new innovation is announced in ML field. Such an extent that number of research papers published … More

activation function, e-swish, keras, swish

A Step by Step Adaboost Example

Adaptive boosting or shortly adaboost is awarded boosting algorithm. The principle is basic. A weak worker cannot move a heavy … More

boosting, decision tree, perceptron

A Step by Step Gradient Boosting Example for Classification

Gradient boosting machines might be confusing for beginners. Even though most of resources say that GBM can handle both regression … More

classification, cross entropy, decision tree, gbm, gradient boosting, iris, softmax

How Pruning Works in Decision Trees

Decision tree algorithms create understandable and readable decision rules. This is one of most important advantage of this motivation. This … More

decision tree, overfitting, pruning

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