Questions tagged [machine-learning]

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

Filter by
Sorted by
Tagged with
3
votes
0answers
932 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
99 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
84 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
190 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
408 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
85 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
1k 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
503 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
185 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
505 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 ...
5
votes
1answer
5k 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
62 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
354 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 ...
7
votes
1answer
86 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
96 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
170 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
492 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
48 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 ...
2
votes
0answers
134 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 ...
8
votes
2answers
403 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
1k 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
79 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
731 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
1k 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 ...
4
votes
0answers
5k 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 ...
3
votes
0answers
358 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
273 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: ...
4
votes
1answer
271 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
103 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
123 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
185 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
377 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
305 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 ...
5
votes
0answers
143 views

Deep learning CNN for image recognition using tensor flow

This algorithm is a convolutional deep neural network used for image recognition. I used the MNIST data set, which is a bunch of images from 0 to 9. As of right now, I have trained this image with ...
3
votes
0answers
4k views

Code for Training a Handwriting Recognition Model

I just made my machine learning code work a few days ago and I would like to know if there's a way to improve my code. Before I get to the implementation of the tasks at hand, I would like to ...
2
votes
0answers
775 views

Optimize GPU usage for real-time object detection from camera with TensorFlow GPU and OpenCV

Trying to recognize objects real time using TensorFlow Object Detection API OpenCV using ssd_mobilenet_v1_coco_11_06_2017 model in GPU. ...
1
vote
0answers
38 views

NER and its F Measure Calculation

I am trying to write one Name Entity Recognition in Hindi. I have primarily used NLTK of Python. I have used HMM Module with its supervised training. The data is annotated and saved in .pos files ...
5
votes
0answers
186 views

Code for training machine learning linear regression and SVM

Ok , for my final year project I've wrote this piece of code to train my machine learning model on a this dataset , here the code i used ...
1
vote
0answers
341 views

Training MLP classifier with TensorFlow on notMNIST dataset

I am new to TensorFlow and I would really appreciate if someone could look at my code to see whether things are done efficiently and suggest improvements. This code works okay and achieves around 91....
3
votes
0answers
248 views

Weighted logistic regression in Julia

I'm trying to estimate a weighted logistic regression as part of a bigger project. I have an implementation in Matlab2015b, but I wanted to give Julia a try to see if I could speed up the estimation ...
7
votes
1answer
888 views

Implementation of linear regression in Python

I wrote an implementation for multivariate linear regression in Python, for data in this link: http://www-bcf.usc.edu/~gareth/ISL/Advertising.csv My main focus is to avoid loops as much as possible ...
3
votes
0answers
76 views

Sklearn: Regularized ridge regression for predicting fantasy football performance from several sources' projections

I've been working on trying to predict fantasy performance of players in this upcoming NFL season based on projections from several experts/sources. I trained the data on projections from last year ...
3
votes
0answers
640 views

Sklearn custom transformer (label encoder and imputer)

I have a pandas.Dataframe with a single (new) record and the following function: ...
6
votes
3answers
9k views

Gradient descent for linear regression using numpy/pandas

I currently follow along Andrew Ng's Machine Learning Course on Coursera and wanted to implement the gradient descent algorithm in python3 using ...
8
votes
2answers
263 views

Trending Machine Learning topics for Alexa

I've created a small Flash Briefing Alexa skill that reports the top 5 trending topics in Machine Learning from the My Bridge service. The feed for the Flash Briefing skill can be pointed to an ...
11
votes
1answer
292 views

Using Support Vector Machine algorithm to analyze satellite image [closed]

I am using Support Vector Machine (SVM) algorithm to perform a classification. The satellite image I am using is really big (5GB) that's why I am trying to take advantage of ...
1
vote
1answer
873 views

MemoryError for a small-ish dataset with RandomForestClassifier()

I have a not-so-big dataset having 100,000 rows and 6k columns and I'm using the following code to fit a Random Forest to it: ...
1
vote
0answers
229 views

sklearn request: pipeline for regression analysis on entering student data

My jupyter notebook is here. I would love to hear any feedback about any problems that may be occurring in my data pipeline. I already know that I still need to develop the following features: ...
5
votes
0answers
739 views

Low accuracy of LSTM model tensorflow [closed]

I am trying to learn LSTM model for sentiment analysis using Tensorflow, I have gone through the LSTM model. Following code (create_sentiment_featuresets.py) generates the lexicon from 5000 positive ...
2
votes
1answer
272 views

Predicting outliers in network data [closed]

I'm implementing KNN algorithm to predict outliers in network data which contains the following columns: source IP address, source port number, protocol and total bytes transferred. To achieve this, I'...