Machine_Learning | Machine Learning | Machine Learning library

I've recently began using an Apple Silicon mac. I installed Tensorflow through Anaconda, version 2.6.2, which was the latest version I could find.

When I run the training code, the training seems to begin initializing, until it reaches some memory error. Then it hangs until I manually stop it.

The printed output looks like:

I want to use xgboost for a classification problem, and two predictors (out of several) are binary columns that also happen to have some missing values. Before fitting a model with xgboost, I want to replace those missing values by imputing the mode in each binary column.

My problem is that I want to do this imputation as part of a tidymodels "recipe". That is, not using typical data wrangling procedures such as dplyr/tidyr/data.table, etc. Doing the imputation within a recipe should guard against "information leakage".

Although the recipes package provides many step_*() functions that are designed for data preprocessing, I could not find a way to do the desired imputation by mode on numeric binary columns. While there is a function called step_impute_mode(), it accepts only nominal variables (i.e., of class factor or character). But I need my binary columns to remain numeric so they could be passed to the xgboost engine.

Consider the following toy example. I took it from this reference page and changed the data a bit to reflect the problem.

create toy data

I am parsing article's and megapost's metrics (likes, views, comments, dates) from the forum.

I am using Selenium and I'm trying to reach the datetime published.

I have attempted to translate pytorch implementation of a NN model which calculates forces and energies in molecular structures to TensorFlow. This needed a custom training loop and custom loss function so I implemented to different one step training functions below.

1. First using Nested Gradient Tapes.

I try to use lemmatize() function from gensim. They said I have to install pattern also to use this function. I have already install both gensim and pattern but every time I try to import lemmatize from gensim, it keeps showing this error

I use pip install gensim and pip install pattern to install the libraries. My gensim version is 4.0.1 and pattern is 3.6

UPDATED

So my goal is to create a machine learning program that takes a list of training numbers given by a user, and try to predict what number they might pick next. I am fairly new to machine learning, and wanted to make this quick project just for fun. Some issues that I am running into include: not knowing how to update my training labels to correspond to training for the next number and how to go about predicting that next number. Here is my current code:

I am attempting to read, then encode items from a csv file, using pandas.

Here is my code:

Based on the question I asked last time: Applying PageRank to a topic hierarchy tree(using SPARQL query extracted from DBpedia)

As I currently got the PageRank value against the Regulated concept map. Toward the concept "Machine_learning", my currently code is below:

I'm trying to make a machine learning model in keras that guesses the next word, given a series of words using a LSTM. This is the code for my model: