Questions tagged [machine-learning]

Machine learning provides computer algorithms that automatically discover patterns in data and make intelligent decisions from them.

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2
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0answers
18 views

Sklearn Custom Imputer from prediction

I asked this question on Stackoverflow, but thought it might be a better fit here. I'm playing around with the titanic dataset, and wanted to create a custom imputer to fill in missing ...
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0answers
30 views

Get most similar element in an array of string with another string

I have a code to get most similar element in an array of categories of jobs to another job using Google's Universal Sentence Encoder. ...
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0answers
20 views

PPE object detection with tensorflow and opencv with rtsp streams

I am working on an object detection API implemented in Tensorflow 1.14 and OpenCV 4.1, where my task is to recognize personal protection equipment (PPE) worn by workers at various construction site ...
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1answer
36 views

Re-write custom feature encoding function python

I have a question regarding code quality and best practices. My task - to write a feature encoding function that will encode categorical labels, boolean labels as one-hot encoding, timestamps for ...
4
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1answer
83 views

Implementation of K-means

I have recently built a class that is an implementation of kMeans from scratch. I believe there is room for improvement and I would happily receive some feedback. The project can be found at: https://...
2
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1answer
51 views

Forecasting stock market data using Support Vector Regression

I coded this Support Vector Regression (SVR) myself following some equations in a journal (see here, or here (not in English)). The loss function used by the journal and the code below is mean ...
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0answers
21 views

Sequential learning function running slowly

I'm new to Python and made this Sequential Learning function but it runs slowly. Do you know why this runs slowly and how to improve it? ...
3
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1answer
58 views

Estimation of min_samples for DBSCAN

I'm attempting to speed up some python code that is supposed to automatically pick the minimum samples argument in DBSCAN. Currently the execution time grows exponentially as the number of training ...
3
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1answer
56 views

Slow python code that automatically selects k for KNNG

This code is used to select K for a K-nearest neighbor graph [KNNG] from a dataset with an unknown number of centroids (which is not the same as K-means clustering). Suppose that you have a dataset ...
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0answers
78 views

Multi-threaded HD Image classifier using a neural network

This is a follow up to the code found here: Multithreaded HD Image Processing + Logistic reg. Classifier + Visualization Description: This code takes a label and a folder path of subfolders as ...
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0answers
142 views

Multithreaded HD Image Processing + Logistic reg. Classifier + Visualization

[I'm awaiting suggestions for improvement/optimization/more speed/general feedback ...] This code takes a label and a folder path of subfolders as input that have certain labels ex: trees, cats with ...
3
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1answer
72 views

Gradient Descent Algorithm using Pandas + GIF Visualization

Happy new year everyone, Following Andrew NG's course on coursera here's my implementation for the gradient descent algorithm(univariate linear regression) in Python using pandas, matplotlib with ...
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0answers
69 views

Keras stacked LSTM model for multiclass classification

I am working on a multiple classification problem and after dabbling with multiple neural network architectures, I settled for a stacked LSTM structure as it yields the best accuracy for my use-case. ...
2
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1answer
63 views

Java Neural Network Implementation

I have recently tried to get a better grip on machine learning from a point of implementation - not statistics. I've read several explanations of an implementation of a Neural Network via pseudocode ...
6
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1answer
135 views

Portfolio optimization using genetic algorithm

I'm working on a (naïve) algorithm for portfolio optimization using GA. It takes a list of stocks, calculates its expected returns and the covariance between all of them and then it returns the ...
2
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1answer
46 views

Optimizing a TFxIDF vectorization - Python 3.x [closed]

I am attempting to train many classifiers to test their performance with classifying tweets as being from a political bot, or not (a binary 0 or 1 classifier). My ...
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0answers
78 views

Homemade web-scraper that feeds perceptron with hidden layer [closed]

I’d like to start by apologising for the mess that is my code. I know that it’s really hard to parse, inefficient, and probably not idiomatic. I just don’t know how to fix it which is why I'm here. ...
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1answer
33 views

How to write a multivariate multi-step forecasting from a multivariate single step [closed]

I'm trying to implement a multi-variate, multiple-step model to forecast the day ahead electricity prices (h+1,h+2,...,h+24). I know how to do one forecast, but I'm confused with how to implement a ...
2
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1answer
50 views

K_nearest_neighbors from scratch [closed]

I wanted to create a script that will perform the k_nearest_neighbors algorithm on the well-known iris dataset. This was mainly for me to better understand the algorithm and process. I think it works, ...
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0answers
52 views

condensed nearest centroid classifier in numpy

This is my attempt to write a numpy-optimized version of a nearest centroid classifier to classify some images from the MNIST data set of handwritten digits. I am ...
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0answers
46 views

Recommender system accuracy testing using GridSearchCV [closed]

I'm trying to improve my Alternating Least Squares (ALS) model performance by testing using different model parameters, but the model performance is seemingly very low. Since the Alternating Least ...
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0answers
67 views

Neural network from scratch in Python

So after watching week 5 of the machine learning course on Coursera by Andrew Ng, I decided to write a simple neural net from scratch using Python. Here's my code: ...
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0answers
50 views

Stochastic gradient descent - backpropagation over mini-batches in one go

I have been working through a tutorial on neural networks. I have then been translating the code to java, to help improve my understanding of what the code is doing. The book mentions a way of ...
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1answer
53 views

Python ANN Implementation [closed]

I recently learned about backpropagation online and tried to implement it. I am not sure I have it correct yet. I am confused and would love a second pair of eyes on this code. Please help me ...
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0answers
64 views

GRU-Autoencoder training

I'm training a GRU auto-encoder and my current code is very slow.I believe it's predict_captions function that takes most the time. Any suggestion to optimize this code? ...
2
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1answer
456 views

Simple Genetic Algorithm in Python

For past few months I was trying to understand genetic algorithms (GA) and most of the materials availble in the web was not always easy for me. Then I came across this article written by Ahmed Gad ...
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2answers
2k views

Simple Linear Regression in C++

Python has amazing sci-kit learn library but I am building some projects on C++ with involves some machine learning algorithms. I found machine learning libraries in C++ involves more dependencies so ...
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0answers
42 views

Automated machine learning training and evaluation in Sagemaker with XGBoost

This code aims to make very easy to train new models in SageMaker and quickly decide whether a new feature should be introduced in our model or not, getting metrics (recall, accuracy and so on) for a ...
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206 views

Reinforcement learning for Acrobot [closed]

I am interesting in reinforcement learning and trying to learn to solve issues with this approach. I chose Acrobot issue from OpenAI gym toolkit for my learning project. Here you can find description ...
2
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1answer
55 views

Manual Regression Tree using Python

I wrote a code to create a regression tree for a synthetic train data of size Np. The idea is, first I have the source node (which consists of all set of points) ...
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0answers
75 views

Machine learning, kNN and Naïve Bayes algorithm

This is the task I am working on: In this assignment you will implement the K-Nearest Neighbour and Naïve Bayes algorithms and evaluate them on a real dataset using the stratified cross validation ...
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0answers
97 views

Plant pest detection using CNN

I am doing a project in plant pest detection using CNN. There are four classes each having about 1400 images. While training the model using Convolution Neural Network, there is a smooth curve for ...
4
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1answer
283 views

Simple decision tree in Haskell

I've been trying to get better at Haskell for a while, and have recently been working on a lot of small projects with it. This constructs a binary decision tree. The command to run it is: ...
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0answers
57 views

Modified and created a new python class for generating a report of metrics for machine learning

I initially posted a question on SO. I have come up with an answer for the same. Basically, given two dicts of models and parameters, user can create an object, and get the report in 5 steps. ...
5
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1answer
62 views

Simple SVM in MATLAB

I'm studying SVMs and wrote a demo in MATLAB (because I couldn't get a quadratic programming package to work correctly in Python). Right now it's simple and can only do linearly-separable cases (...
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0answers
120 views

Chess Agent using reinforcement learning with monte carlo tree search

I wanted to ask if this project is valid to state on a resume for entry-level python developer and if the code is presentable to say a job interviewer. github link: full project (If this is not the ...
2
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1answer
59 views

User-Interactive Data Cleaning Program in Python

I'm trying to develop a program in Python that allows the user to import datasets and perform operations on them using pandas and numpy so she/he can skip writing all the preprocessing code her/...
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1answer
48 views

A simple clusterness measure of data in one dimension using Java

Problem definition Given \$X = (x_1, \dots, x_n)\$ such that \$x_1 \leq x_2 \leq \dots \leq x_n \$. Let \$x_{\min} = \min X = x_1\$, \$x_{\max} = \max X = x_n\$ and \$r = x_{\max} - x_{\min}\$. Also, ...
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1answer
466 views

Predicting credit card default

I have this code for predicting credit card default and it works perfectly, but I am checking here to see if anybody could make it more efficient or compact. It is pretty long though, but please bear ...
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0answers
437 views

A simple toy ResNet model and its implementation

I want to understand how resnet works also called us residual networks and I understand it better when I code one myself. I tried to find a simple implementation of resnet in the web but most I found ...
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0answers
87 views

Posterior collapses in an RNN variational auto-encoder - PyTorch

I am trying to implement and train an RNN variational auto-encoder as the one explained in "Generating Sentences from a Continuous Space". Although I apply their proposed techniques to mitigate ...
4
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1answer
61 views

Set of one-hot encoders in Python

In the absence of feature-complete and easy-to-use one-hot encoders in the Python ecosystem I've made a set of my own. This is intended to be a small library, so I want to make sure it's as clear and ...
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0answers
41 views

Custom Vector and Matrix classes in python for machine learning

I am creating a machine learning tool set from scratch in python. I have never done something of this kind and I don't usually use python but I thought it would be good to expand my horizons. I am ...
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0answers
199 views

Tensorflow model for predicting dice game decisions

For my first ML project I have modeled a dice game called Ten Thousand, or Farkle, depending on who you ask, as a vastly over-engineered solution to a computer player. You can find the complete game, ...
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0answers
57 views

Get stacked game state in NHWC format

After reading this, I decided to transition my DQN code from the keras library to tf.keras library (code is located in this repo) and my original code used NCHW format, as it was faster with GPUs. As ...
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0answers
872 views

Auto classification of my bank transactions

This is my first Machine Learning algorithm using Python and SkLearn. The code works, which is pretty awesome. I'm getting about 65-70% of accuracy after training it with about 4k rows of data. ...
5
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1answer
313 views

Reinforcement Learning for Flappy Bird in JavaScript

To give a bit of a background, I'm organizing a small session about reinforcement-learning, specifically Q-learning, to a group of high school students in the ...
2
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0answers
132 views

Simple Neural Network from scratch using NumPy (Python)

I added learning rate and momentum to a neural network implementation from scratch I found at: https://towardsdatascience.com/how-to-build-your-own-neural-network-from-scratch-in-python-68998a08e4f6 ...
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0answers
374 views

Principal Component Analysis in Tensorflow

To learn the low-level API of Tensorflow I am trying to implement some traditional machine learning algorithms. The following Python script implements Principal Component Analysis using gradient ...
4
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1answer
3k views

k-means using numpy

This is k-means implementation using Python (numpy). I believe there is room for improvement when it comes to computing distances (given I'm using a list comprehension, maybe I could also pack it in a ...