Questions tagged [machine-learning]
Machine learning provides computer algorithms that automatically discover patterns in data and make intelligent decisions from them.
160
questions
1
vote
0answers
26 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 ...
-1
votes
1answer
31 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 ...
0
votes
0answers
24 views
Speed up auto encoder training without breaking anything
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
votes
1answer
69 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 ...
1
vote
2answers
71 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 ...
3
votes
0answers
26 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 ...
0
votes
0answers
31 views
Reinforcement learning for Acrobot
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 ...
1
vote
1answer
39 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) ...
2
votes
0answers
73 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 ...
2
votes
0answers
76 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
votes
1answer
129 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:
...
1
vote
0answers
35 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.
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5
votes
1answer
45 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 (...
1
vote
0answers
101 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
votes
1answer
55 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/...
0
votes
1answer
40 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, ...
0
votes
1answer
268 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 ...
3
votes
0answers
194 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 ...
1
vote
0answers
64 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
votes
1answer
52 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 ...
1
vote
0answers
34 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 ...
1
vote
0answers
107 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, ...
1
vote
0answers
46 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 ...
3
votes
0answers
570 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
votes
1answer
216 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
votes
0answers
98 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
...
2
votes
0answers
259 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 ...
3
votes
1answer
1k 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 ...
2
votes
0answers
59 views
Simple linear regression of two variables
This is the code I built to implement a simple linear regression to check the impact of variable A on B. I am not interested in predicting that's why the statistical approach is important for me to ...
3
votes
1answer
271 views
BipedalWalker-v2 one-step actor-critic agent trains slow
I'm trying to solve the OpenAI BipedalWalker-v2 by using a one-step actor-critic agent. I'm implementing the solution using python and tensorflow. My question is whether the code is slow because of ...
6
votes
1answer
77 views
Random Weighted Classifier in R
I am computing a random weighted classifier based on the rates at which 3 labels appear in a "train" set. I want to use this RWC as a baseline for other classifiers. I'm doing this over 1000 ...
6
votes
1answer
69 views
Simple neural network implementation in Python
A simple neural network I wrote in Python without libraries. I avoided implementing it in matrix form because I sought to get a basic understanding of the way NN's work first. For that reason I'm ...
3
votes
2answers
94 views
How to make my neural network train faster
I'm trying to train my neural network and for the most part it's going well. However, I'd like it if it could train faster and was wondering if anyone could give some advice.
I'm trying mostly to ...
6
votes
1answer
148 views
Python class for organizing images for machine learning
I built a class to help me handle image data to use in machine learning. I thought that there would be a pre-existing package that did what I wanted but I couldn't find it so I wrote this. I am not ...
2
votes
1answer
45 views
Basic Single Header statistics and ml libray for C++ - Scikit-Learn like implementation
I am developing scikit-learn like implementation for C++ it is in the initial stage while developing I've started doubt myself that is this the correct implementation, since here accuracy is more ...
1
vote
0answers
98 views
Neural Network Backpropagation
My neural network is buggy somewhere. However, the reason I am posting here and not Stack Overflow is because a buggy neural network can still be trained to some degree and will compile/perform better ...
9
votes
2answers
233 views
Univariate linear regression from scratch in Python
I am relatively new to machine learning and I believe one of the best ways for me to get the intuition behind most algorithms is to write them from scratch before using tons of external libraries.
...
2
votes
0answers
926 views
Logistic Regression using PyTorch
I want to get familiar with PyTorch and decided to implement a simple neural network that is essentially a logistic regression classifier to solve the Dogs vs. Cats problem.
I move 5000 random ...
1
vote
0answers
71 views
Predicting Disaster (Titanic)
Intro
I have started a new course (Analyzing Big Data with Microsoft R) and have an exam soon.
So I wanted to test my skills, and a nice way to do this was by doing a Kaggle competition Titanic: ...
4
votes
1answer
288 views
Naive Bayesian Algorithm in Python with cross-validation
I've wrote this code to evaluate a Machine Learning - the classification problem for digits recognition as in the figure below:
For more details and to check the whole code, check the GitHub ...
8
votes
1answer
789 views
Genetic algorithm for playing Tetris
Readme.md
Tetris
In my quest to building a Tetris game, where you can challenge an AI, I have created and trained an AI that plays Tetris all by himself. Github link I think the easiest way to run ...
2
votes
0answers
416 views
Simple Neural Network in C
A neural network is a structure of connections and nodes that takes input and generates an output. It can be "taught"(adjusting weights and biases of connections) from a teacher data set with ...
4
votes
0answers
327 views
Tic Tac Toe engine in Python for Deep Learning
I'm implementing a Tic Tac Toe engine that will work with deep learning. I'm using a 3x3 numpy array of floats to represent the board. +1.0 represents an X, ...
4
votes
0answers
246 views
Linear Regression in Tensorflow
I am a machine learning newbie and recently I implemented (or at least tried to implement) a linear regression model in tensorflow. I would love to know how I can improve my code:
...
5
votes
1answer
204 views
Linear Regression on random data
Wrote a simple script to implement Linear regression and practice numpy/pandas. Uses random data, so obviously weights (thetas) have no significant meaning. Looking for feedback on
Performance
Python ...
3
votes
2answers
85 views
Inefficient Regularized Logistic Regression with Numpy
I am a machine learning noob attempting to implement regularized logistic regression via Newton's method.
The example data have two features which are to be expanded to 28 through finding all ...
1
vote
0answers
112 views
Chainer - Python - Logistic Regression
I created a simple Logistic Regression model using Python and Chainer. I would like to optimize the code for which I like to get some help.
One restriction: interchanging the implemented ...
0
votes
1answer
163 views
Greedy adaptive dictionary (GAD) for supervised machine learning [closed]
For my project in machine learning supervised, I have to simplify a training-data and I have to use this technique at page 5 of the document.
Pseudocode algorithm
My code (numbers are the steps):
<...
3
votes
0answers
340 views
PCA, LDA and Logistic Regression
Based on the great blog by Joel Grus, I implemented LogisticRegression, PCA, and LDA. I'd appreciate feedback as I'm not sure that the logistic classifier is good enough (as it supposed to achieve ...
5
votes
1answer
259 views
Facial recognition tool
I created a small library and an example application in Python for learning about facial recognition and experimenting with it. Right now though, I am loading a list of file names into memory and then ...
