Automate a Causal Inference Python Repo from Scratch with Augment Code If you’ve ever wanted to build a clean Python repository for implementing methods from Causal Inference for the Brave and True but didn’t want to do all the setup manually, you might love using Augment Code. It is a platform that connects AI to […]
Agent Code Generation Part 1: Augment Code Read More »
Here is how you can call OpenAI’s ChatGPT API, given that you have an API key. Follow these instructions to get one. import openai openai.api_key = 'FILL IN YOUR OWN' openai.ChatCompletion.create( model="gpt-3.5-turbo", messages=[ {"role": "system", "content": "You are a helpful assistant."}, {"role": "user", "content": "Who won the world series in 2020?"}, {"role": "assistant", "content": "The
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https://pyro.ai/examples/intro_long.html
Pyro’s introduction to probabilistic programming Read More »
Yes, this is clearly nonsense. Sorting is not a hard problem and standard algorithms such as quicksort and mergesort have O(x^2) and O(n log(n)) complexity. But let me scratch this itch of sorting numbers using an evolutionary algorithm, specifically Covariance matrix adaptation evolution strategy (CMA-ES). Technically, we will use what I think is the original
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The aim is to produce a plot like this. The orange line is your data, the green line is the upper "bollinger" band, the blue line is the lower "bollinger" band. The red dots indicate where your data is either above or below the bands. Copy-paste this code: import pandas as pd import numpy as
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I’m interested in object detection and other computer vision tasks. For example, I’m working on a teddy-bear detector with my son. So, how do you quickly download images for a certain category? You can use this approach that I learned from a course on Udemy. In the above example, the crawler will find images in
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Here is how to sample from a softmax probability vector at different temperatures. import numpy as np import matplotlib.pyplot as plt import matplotlib as mpl import seaborn as sns mpl.rcParams[‘figure.dpi’]= 144 trials = 1000 softmax = [0.1, 0.3, 0.6] def sample(softmax, temperature): EPSILON = 10e-16 # to avoid taking the log of zero #print(preds) (np.array(softmax)
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I have adapted an example neural net written in Python to illustrate how the back-propagation algorithm works on a small toy example. My modifications include printing, a learning rate and using the leaky ReLU activation function instead of sigmoid. import numpy as np # seed random numbers to make calculation # deterministic (just a good
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I work in the ad tech industry, which means that I track people online for a living. Mainly, I do it because the industry has interesting computer science problems and because the job pays well. I will not defend ad tech. Mainly because ad tech is not important enough to humanity to defend. However, I
No one in ad tech needs to know your name Read More »
I like to dabble with machine learning and specifically neural networks. However, I don’t like to wait for exorbitant amounts of time. Since my laptop does not have a graphics card that is supported by the neural network frameworks I use, I have to wait for a long time while my models git fitted. This
Neural networks on GPUs: cost of DIY vs. Amazon Read More »