January 2023 - cypherpunks - lists.cpunks.org

[crazy] TrObumampa Won: Detecting Fake News with Python and Machine Learning
by Undescribed Horrific Abuse, One Victim & Survivor of Many 08 Jan '23

08 Jan '23

https://data-flair.training/blogs/advanced-python-project-detecting-fake-ne… Detecting Fake News with Python and Machine Learning Do you trust all the news you hear from social media? All news are not real, right? How will you detect fake news? The answer is Python. By practicing this advanced python project of detecting fake news, you will easily make a difference between real and fake news. Before moving ahead in this machine learning project, get aware of the terms related to it like fake news, tfidfvectorizer, PassiveAggressive Classifier. Also, I like to add that DataFlair has published a series of machine learning Projects where you will get interesting and open-source advanced ml projects. Do check, and then share your experience through comments. Here is the list of top Python projects: Fake News Detection Python Project Parkinson’s Disease Detection Python Project Color Detection Python Project Speech Emotion Recognition Python Project Breast Cancer Classification Python Project Age and Gender Detection Python Project Handwritten Digit Recognition Python Project Chatbot Python Project Driver Drowsiness Detection Python Project Traffic Signs Recognition Python Project Image Caption Generator Python Project What is Fake News? A type of yellow journalism, fake news encapsulates pieces of news that may be hoaxes and is generally spread through social media and other online media. This is often done to further or impose certain ideas and is often achieved with political agendas. Such news items may contain false and/or exaggerated claims, and may end up being viralized by algorithms, and users may end up in a filter bubble. What is a TfidfVectorizer? TF (Term Frequency): The number of times a word appears in a document is its Term Frequency. A higher value means a term appears more often than others, and so, the document is a good match when the term is part of the search terms. IDF (Inverse Document Frequency): Words that occur many times a document, but also occur many times in many others, may be irrelevant. IDF is a measure of how significant a term is in the entire corpus. The TfidfVectorizer converts a collection of raw documents into a matrix of TF-IDF features. What is a PassiveAggressiveClassifier? Passive Aggressive algorithms are online learning algorithms. Such an algorithm remains passive for a correct classification outcome, and turns aggressive in the event of a miscalculation, updating and adjusting. Unlike most other algorithms, it does not converge. Its purpose is to make updates that correct the loss, causing very little change in the norm of the weight vector. Detecting Fake News with Python To build a model to accurately classify a piece of news as REAL or FAKE. About Detecting Fake News with Python This advanced python project of detecting fake news deals with fake and real news. Using sklearn, we build a TfidfVectorizer on our dataset. Then, we initialize a PassiveAggressive Classifier and fit the model. In the end, the accuracy score and the confusion matrix tell us how well our model fares. The fake news Dataset The dataset we’ll use for this python project- we’ll call it news.csv. This dataset has a shape of 7796×4. The first column identifies the news, the second and third are the title and text, and the fourth column has labels denoting whether the news is REAL or FAKE. The dataset takes up 29.2MB of space and you can download it here. Project Prerequisites You’ll need to install the following libraries with pip: pip install numpy pandas sklearn You’ll need to install Jupyter Lab to run your code. Get to your command prompt and run the following command: C:\Users\DataFlair>jupyter lab You’ll see a new browser window open up; create a new console and use it to run your code. To run multiple lines of code at once, press Shift+Enter. Steps for detecting fake news with Python Follow the below steps for detecting fake news and complete your first advanced Python Project – Make necessary imports: import numpy as np import pandas as pd import itertools from sklearn.model_selection import train_test_split from sklearn.feature_extraction.text import TfidfVectorizer from sklearn.linear_model import PassiveAggressiveClassifier from sklearn.metrics import accuracy_score, confusion_matrix Screenshot: importing data sets in python open source projects 2. Now, let’s read the data into a DataFrame, and get the shape of the data and the first 5 records. #Read the data df=pd.read_csv('D:\\DataFlair\\news.csv') #Get shape and head df.shape df.head() Output Screenshot: interesting python projects - read data frame 3. And get the labels from the DataFrame. #DataFlair - Get the labels labels=df.label labels.head() Output Screenshot: Python projects examples - get labels 4. Split the dataset into training and testing sets. #DataFlair - Split the dataset x_train,x_test,y_train,y_test=train_test_split(df['text'], labels, test_size=0.2, random_state=7) Screenshot: Python data science projects - split data sets 5. Let’s initialize a TfidfVectorizer with stop words from the English language and a maximum document frequency of 0.7 (terms with a higher document frequency will be discarded). Stop words are the most common words in a language that are to be filtered out before processing the natural language data. And a TfidfVectorizer turns a collection of raw documents into a matrix of TF-IDF features. Now, fit and transform the vectorizer on the train set, and transform the vectorizer on the test set. #DataFlair - Initialize a TfidfVectorizer tfidf_vectorizer=TfidfVectorizer(stop_words='english', max_df=0.7) #DataFlair - Fit and transform train set, transform test set tfidf_train=tfidf_vectorizer.fit_transform(x_train) tfidf_test=tfidf_vectorizer.transform(x_test) Screenshot: python data science projects 6. Next, we’ll initialize a PassiveAggressiveClassifier. This is. We’ll fit this on tfidf_train and y_train. Then, we’ll predict on the test set from the TfidfVectorizer and calculate the accuracy with accuracy_score() from sklearn.metrics. #DataFlair - Initialize a PassiveAggressiveClassifier pac=PassiveAggressiveClassifier(max_iter=50) pac.fit(tfidf_train,y_train) #DataFlair - Predict on the test set and calculate accuracy y_pred=pac.predict(tfidf_test) score=accuracy_score(y_test,y_pred) print(f'Accuracy: {round(score*100,2)}%') Output Screenshot: python machine learning projects 7. We got an accuracy of 92.82% with this model. Finally, let’s print out a confusion matrix to gain insight into the number of false and true negatives and positives. #DataFlair - Build confusion matrix confusion_matrix(y_test,y_pred, labels=['FAKE','REAL']) Output Screenshot: python projects - confusion matrix So with this model, we have 589 true positives, 587 true negatives, 42 false positives, and 49 false negatives. Summary Today, we learned to detect fake news with Python. We took a political dataset, implemented a TfidfVectorizer, initialized a PassiveAggressiveClassifier, and fit our model. We ended up obtaining an accuracy of 92.82% in magnitude. Hope you enjoyed the fake news detection python project. Keep visiting DataFlair for more interesting python, data science, and machine learning projects. Your opinion matters Please write your valuable feedback about DataFlair on Google | Facebook

1 0

[ot][spam][crazy] coping spam while trying to make code to prompt a model
by Undescribed Horrific Abuse, One Victim & Survivor of Many 08 Jan '23

08 Jan '23

gibberish ! gibbering gibberish!

1 63

Anarchapulco 2023 Starting February 6th
by professor rat 08 Jan '23

08 Jan '23

No matter what happens to KGB Russia you and Juan will still share your undying love for Ron Paul, G.

1 0

Lady GaGa investigates Jan6
by professor rat 08 Jan '23

08 Jan '23

Or was that Gramps? I get them mixed up.

1 0

Cryptocurrency: Helium Network Guerrilla RF Antennas Popping Up Everywhere
by grarpamp 08 Jan '23

08 Jan '23

Mysterious Antennas Found In Utah's Hills; Some Speculate 'Decentralized' Blockchain Network https://ksltv.com/516749/why-are-antennas-popping-up-all-over-the-foothills… Salt Lake City officials are finding mysterious antennas across the foothills of the Salt Lake City metropolitan area. The first ones were discovered nearly a year ago, but more have been popping up in recent months. These devices appear to be relaying data across a wide area. As first reported by KSLTV 5 in Utah, the mysterious devices consist of a battery box, a solar panel, and an antenna. "These towers have been bolted into different peaks and summits and ridges around the foothills," Tyler Fonarow, the city's recreational trails manager, explained, "and it started with one or two, and now it might be as much as a dozen." Salt Lake City public lands officials hiked up the snowy Twin Peaks trail today to remove a mysterious device (solar panel, antenna & locked battery box). They're finding more in the foothills, with no explanation as to who's putting them there -- or why. Story on @KSL5TV at 6 pic.twitter.com/llfFXMOyLq — Michael Locklear (@MichaelLocklear) January 5, 2023 Fonarow said whoever is installing these small fiberglass antennas doesn't have a permit for authorization on public land. His department has been seizing the devices. They found one last week and plan to remove another later this month. More antennas have been found on property managed by the Forest Service and the University of Utah. A university spokesperson just released a statement about the mysterious antennas: "Since Salt Lake City leaders alerted the University of Utah to the unauthorized solar panel towers in the foothills northeast of the Avenues neighborhood, University of Utah representatives have been actively coordinating with City Public Lands officials to determine whether any member of our campus community is connected to the towers. As far as we know, the tower located on university property is not owned or operated by the university. We appreciate Salt Lake City's collaboration and dedicated efforts to identify the owners." Fonarow speculated the devices could be part of a decentralized wireless connectivity platform: "It might be related to cryptocurrency and relaying networks and being able to make money off that," he said, "so that's another reason we want to stop it now before it becomes a dumping ground for dozens and dozens of more antennas." Last week, a Salt Lake City Public Lands Facebook posted pictures of "unauthorized solar panel towers" found in the Foothills. Some people who replied to the Facebook post speculated the devices could be part of the Helium network. "Probably helium network like several have posted. Or some kind of mesh network repeaters? I don't understand why they are being torn down and huge effort to take them off public lands, when if it is a mesh network repeater, can be used by the public, and is very important in emergency/communication failure situations," one person said. "Those are very clearly off-grid Helium miners," another person said. Someone asked: "Ham radio repeater?" If the speculation is correct, these mysterious antennas could be hotspots connecting to a wireless blockchain-based network for Helium. This entirely new incentive model allows people to set up hotspots that act as Helium miners and serve data to devices. People can earn money by simply buying a hotspot and plugging it in. Here's what the Helium coverage looks like around Salt Lake City. There are nearly a million hotspots nationwide. "Mining HNT is done by installing a simple device on your home or office window," Helium wrote on their website, adding these "hotspots provide miles of wireless network coverage for millions of devices around you using Helium LongFi, and you are rewarded in HNT for doing this. And because of an innovative proof-of-work model (we call it "Proof-of-Coverage"), your Hotspot only uses 5W of energy." There's no confirmation Helium hotspots are the devices being found by officials, but speculation indeed points to that.

1 0

Anarchapulco 2023 Starting February 6th
by grarpamp 08 Jan '23

08 Jan '23

https://anarchapulco.com/ Anarchapulco - February 6-10th, 2023 Agoraforko - February 11-18th, 2023 And more including... Jeff Berwick The Dollar Vigilante Ron Paul The Ron Paul Liberty Report Larken Rose The Most Dangerous Superstition Max Igan The Crowhouse Del Bigtree Highwire Podcast Dan Dicks Press For Truth Michael Cobb ECI Development Eileen McKusick Biofield Tuning Mark Passio What on Earth is Happening - Virtual Speaker Andrew Kaufman Terrain: The Film Vit Jedlicka Liberland Dr. Carrie Madej Human 2.0 Whistleblower Brendan Murphy Truthiverse Podcast Colin Cantrell Nexus Shunyamurti Sat Yoga - Virtual Speaker Marjory Wildcraft The Grow Network Charlie Robinson Macroaggressions Podcast Rafael Laverde The Crypto Vigilante Samantha Pilbeam The Quantum Questions Greg Garrett The Quantum Questions James Fry GrowEverywhere.com Chad Schwartz Sovereign Life Skills Becca Tzigany Venus and Her Lover Not Governor Patrick Smith Anarchast Yolande Norris-Clark Radical Birth Keeper School Chris Horlacher Fighting the Five Eyes Dr. Sarah Grace Manski The Spatial Web/Metaverse Kalina Lux $DERO Maryam Henein HoneyColony Danny Sessom The Crypto Show parazyd DarkFi Juan Castro Soto Tumin Rocelo Lopes SmartPay Michael Fitzgerald Stoic.XMR: The Monero Standard skoupidi DarkFi Mateo MAD Cripto MAD Cripto Topher Field Good People Break Bad Laws - Virtual Speaker Cory Michelle Identity Transformation Coach - Virtual Speaker Pastor Artur Pawlowski Street Church - Virtual Speaker Belegui Elanor Volunteer Firefighter David DuByne ADAPT 2030 - Virtual Speaker Everet Dee Mysterium Academy - Virtual Speaker Tracy is Magic Reifferscheid Tracy is Magic - Virtual Speaker Glenn Meder Privacy Action Plan - Virtual Speaker David Whitehead Truth Warrior - Virtual Speaker Honourable A. Brian Peckford British Columbia - Virtual Speaker Agnieszka Evenson Evenson Sovereign Body Language

1 0

the war in russia and the jewnazi grancrap - grarpamp @ gmail.com
by punk 07 Jan '23

07 Jan '23

When grancrap talks about the demrats we can hear very loud hysterical screeches accusing the demrats of being 'the far left'. Listening to grancrap's hysterical screeches one would assume that grancrap himself isn't a demrat. I mean he's trying to sound like he doesn't like them...? Consider now the current US war against russia, fought for world domination. The war was started in 2014 by the demrat obomba and put into high gear by the demrat biden in 2022 - the two supreme demrat commanders. It's rather clear that demrats are the most insane, anti-human warmongers in the known universe. And now it gets really amusing, because the anti-human jewnazi grancrap who pretends to hysterically whine about the demrats, is the same anti-human jewnazi who ONLY PARROTS BIDEN WAR PROPAGANDA. Yeah, the only thing grancrap does is parrot anti-russia, PRO-BIDEN-PENTAGON PROPAGANDA.

1 0

Visible light communication - Wikipedia
by Gunnar Larson 07 Jan '23

07 Jan '23

https://en.wikipedia.org/wiki/Visible_light_communication In telecommunications, visible light communication (VLC) is the use of visible light (light with a frequency of 400–800 THz/wavelength of 780–375 nm) as a transmission medium. VLC is a subset of optical wireless communications technologies.

1 0

Platform Technology - ShotSpotter
by Gunnar Larson 07 Jan '23

07 Jan '23

https://www.shotspotter.com/precision-policing-platform-technology/ For 21st century law enforcement to succeed agencies need to be evidence-based, proactive, and community-minded. Learn how our Precision Policing Platform, which encompasses our Respond, COPLINK X, Investigate, and Connect products, ultimately enables departments to meet their goals.

1 0

[spam][crazy] The need for rational feedback when irrational
by Undescribed Horrific Abuse, One Victim & Survivor of Many 07 Jan '23

07 Jan '23

Not much text to add here, but I was thinking on how precious rational feedback from expressions is, and how rare; and also how hard it is to provide this reliably, when the person (I was actually thinking myself here, but professor rat could be an example the other way as i rarely understand what he says) does not seem to be expressing rationally at all. It's still so important. I spend a lot of daydreaming and attempting around producing systems that will respond to me rationally, in any way at all. (the current mainstream AI approach kind of pointedly avoids enforcing rationality. this lets language models more easily hold disparate beliefs.)

1 0