Advice and tutorials for programmers
We’re all accustomed to visualising data in images/graph. Whether it’s the price of a company stock going up and down, or the number of customers in the quarter. We know how data is represented. But what about other ways to present data?
If you’re a beginner in deep learning and find it too slow to run the tutorials, or perhaps you faced a “CUDA” related error — don’t worry. Google Colaboratory (Google Colab) is a free and straightforward solution
You may have encountered this acronym if you’re studying Machine Learning (ML) and specifically Natural Language Processing (NLP). “TF-IDF”. I keep finding it in every research paper I read about automatic text summarization
Introduction to sentence segmentation, tokenization, stop word removal, stemming, and lemmatization. This article will explain five processes applied to written content in the “Pre-processing” step — the first and critical step in Natural Language Processing (NLP). I’ll consider only the English language
Bayes theorem, invented by Thomas Bayes in the 18th century, describes a simple and powerful methodology for calculating the probability of a belief/hypothesis occurring given a new piece of evidence/observation. Throughout history, the Bayes theorem has been applied to find nuclear bombs and is the basis for machine learning algorithms (classifiers). It’s used in spam filtering, self-driving cars, to access financial risk and more. The algorithms can accurately identify the probability of an event occurring and therefore make good decisions
When screen readers are not enough.
I’m impressed by how sensors can make up for a lost one (e.g. hearing for lost vision) and how other parts of the body can serve as a means for receiving information and basically create a totally new sensor..
Introduction to python generator functions. A regular function in Python processes all the values, holds them in memory and returns them to the caller. Instead, a generator function doesn’t hold in memory — it generates the values over time as the caller requests them.
Python is a great language for those starting in coding. You can install and quickly start programming in a matter of minutes. If you’re learning to code and entering the field of machine learning or data science in general, there is no better language than Python. Among other characteristics, it contains powerful libraries for efficiently managing data (collection, extraction, cleaning) — that’s a key reason for being so popular.
Why it’s called “regression,” how to find the regression line (intuition), and how to measure how good it is. It’s time to take two steps back in my machine learning journey and dive into the math, algorithms, and intuition behind the scenes. It’s been fun to learn frameworks such as PyTorch, TensorFlow, and the Python language itself. But I realize I’m always getting stuck and having to circle back to understand things better. I want to close this gap.
Implementation in Python. Is it better to take the three or quick two-plus intentional foul? Monte Carlo Simulation is a type of simulation where the events are chosen to happen randomly. By iterating and trying out various outcomes many times, arbitrarily, it gives great confidence in the result. [1] The name comes from Monte Carlo, located in Monaco, known for its strong gambling activity
Programmers Branch 