No major Western mainstream media outlet reported the Palestinian woman from Gaza who said Israeli prison guards raped her four times in one week.
Yet they relentlessly amplified October 7 rape stories that were fabricated.
#FreeCongo🇨🇩
Children, women and men in Congo risk death mining cobalt for our phones and electric cars. Many have already died. This genocide is ignored while Big Tech companies profit from exploitation and consumerism. We can no longer look away. Write “Free Congo" SPEAK UP!
We are so cooked as a generation, because what do you mean you can love and provide for your child only when you are on good terms with the mother?
So, should a mother only love her child when she’s good with the father?
Oh God, how I hate selfish deadbeat fathers!!!!!!!
Black children experience racism from birth. But it’s white women on here arguing that white people should be forgiven bc they’re no longer racist.
Man get tf out my face. Fuck them people and I hope this family is okay.
51 Muslims were killed when Christian terrorist Brenton Tarrant attacked two mosques in Christchurch New Zealand, during Jumu’ah prayers.
He killed 51 Muslims and attempted to murder another 40. His victims included men, women and children who had gathered to worship.
Innocent people were murdered simply because they were Muslims. They were praying, not hurting anyone.
So what you gonna say about that Malama munafuka?
Day 4 of Making AI Make Sense
Topic: Data Preparation
Before a machine learning model can learn, we must prepare the data.
𝘉𝘶𝘵 𝘸𝘩𝘺 𝘥𝘰 𝘸𝘦 𝘯𝘦𝘦𝘥 𝘵𝘰 𝘱𝘳𝘦𝘱𝘢𝘳𝘦 𝘵𝘩𝘦 𝘥𝘢𝘵𝘢?
Raw data is messy, it has words, missing information, typos, and empty cells
In traditional machine learning, models learn by finding mathematical relationships between specific input measurements (features) and target output(labels). A model can’t find mathematical relationships between empty spaces or compute words and numbers in an equation to produce sensible results.
Noisy data forces the machine to copy the flaws of the training dataset instead of recognizing genuine patterns. This is called “overfitting”, a situation whereby a model “memorizes”, rather than “learns”.
If info is missing, the model wouldn't have enough to work with. If you feed it inaccurate info, it memorizes the mistakes in it and produces wrong output when working with data outside of its training set. This model is said to be “overfit.”
A way of avoiding model overfitting is carefully preparing the data
𝘉𝘶𝘵 𝘩𝘰𝘸 𝘥𝘰 𝘸𝘦 𝘱𝘳𝘦𝘱𝘢𝘳𝘦 𝘵𝘩𝘦 𝘥𝘢𝘵𝘢?
There are a few steps to follow when preparing data for a model to learn from. These include, data cleaning, feature engineering, data splitting, etc.
But the very first part is data cleaning. Which involves handling missing values, text noise, and corrupted entries. Each is handled differently.
𝘚𝘰 𝘩𝘰𝘸 𝘥𝘰 𝘸𝘦 𝘤𝘭𝘦𝘢𝘯 𝘰𝘶𝘳 𝘥𝘢𝘵𝘢?
For missing values,
→ raw datasets are inspected to detect invalid records, empty entries, or noise before training. This is the data scrubbing process.
→ missing blanks are filled through imputation rather than removing the whole record. For example, if a value is missing, data scientists estimate a reasonable substitute, mostly by calculating a typical value from the remaining dataset.
For messy text data,
→ The text must be “normalized” (like lowercasing and removing punctuation) so the differences don't confuse the model.
→ Duplicate words that have semantically the same meaning are removed and all words are left in their base form.
→ The texts are then represented numerically using a couple of encoding techniques. These numbers are what the model computes when learning from text data.
Tomorrow, we'd talk about feature engineering and data splitting more
@httpleem Unemployment and poverty affect everyone, yes. But men are pressured to build wealth to survive it, while women are socially conditioned to marry into it. A bad economy doesn't erase gender-specific expectations it exaggerates them.
I’d open my phone every new day and find another “trending” femicide case. Women are being killed every day!
Today, it’s a man from Anambra; yesterday’s was from Kogi. How long are we supposed to live in fear and terror? Is Nigeria not terrible enough?
rihanna forgiving him was her personal choice and part of her healing process. her forgiveness doesn’t mean the rest of us have to forgive him, which is something she even said. chris also has a history of abuse, so we don’t need to let anything go.
Some of the married female nurses I've worked with are more than qualified to practise abroad. They have good IELTS results, have prepared their documents and are ready to take the next step.
But guess what's holding some of them back? Their husbands don't want them to leave Nigeria.
@httpleem I don’t think I know they are I know they are !
When a society makes financial independence nearly impossible for women and preaches marriage as the ultimate payday, choosing a wealthy older man isn't a moral flaw it’s survival
Touch grass
Men understand that Peller, who is 21, “has an underdeveloped frontal lobe, and he has caged himself by getting married so young because he hasn't explored life”
But a 21-year-old girl is fit to be a wife and mother because, hahahha, “women mature very fast.”
Logic e choke 👏
Male humor is implying that penetrative sex is degrading and whoever is at the receiving end is being “defeated”. This is how rape culture is casually enforced through sports and then we wonder why male athletes get so much support from fans when they end up abusing women