A collection of random ideas so I don't have to google again
© 2018 - 2023 A collection of random ideas so I don't have to google again
Building Your Own Personal Assistant With ChatGPT
If you’ve ever used Siri, Alexa, or Google Assistant, you know how powerful and convenient having a personal assistant can be. What if you could build your own personal assistant, tailored to your specific needs? Thanks to the power of OpenAI’s ChatGPT language model and the open-source community, you can!
In this post, we’ll explore a GitHub project called “ChatGPT-chan,” which provides a collection of tools to help you build your own personal assistant.
3 minutes read
Hudson and Thames mlfinlab stuff
Dockerfile FROM python:3.8-slim-buster RUN apt update && apt install git -y RUN apt install -y build-essential g++ libgl1-mesa-glx libx11-6 cmake protobuf-compiler -y RUN python -m pip install jupyter cvxpy RUN git clone https://github.com/rushic24/mlfinlab.git && cd mlfinlab && python setup.py install RUN pip install pandas==1.5.2 tqdm statsmodels==0.13.5 numpy==1.23.5 EXPOSE 8890 ENTRYPOINT [ "jupyter", "notebook", "--no-browser", "--port=8890", "--ip=0.0.0.0", "--allow-root" ] Makefile # Specify the name of the image IMAGE_NAME = "mlfinlabstuf" # Specify the path to the Dockerfile DOCKERFILE_PATH = ".
1 minutes read
Collaborative Filtering on Amazon Products With PySpark
Goals Recommend top 5 products for an user: RMSE = 1.22 Data set description This is a list of over 34,000 consumer reviews for Amazon products like the Kindle, Fire TV Stick, and more provided by Datafiniti’s Product Database. The dataset includes basic product information, rating, review text, and more for each product. Note that this is a sample of a large dataset. The full dataset is available through Datafiniti. from pyspark.
4 minutes read
Golden Hour of Publishing Comments
Hacker News is a site similar to Reddit where user-submitted stories (known as “posts”) are voted on and commented on. In the tech and startup worlds, Hacker News is immensely popular, and pieces that reach the top of the site’s listings can get hundreds of thousands of views.
We’ll compare these two types of posts to determine the following: 1. Do ‘Ask HN’ or ‘Show HN’ posts receive more comments on average?
6 minutes read
Modeling and Analysis of One Finger QWERTY Keyboard Typing Using Fiit's and Zipf's Laws
Goals 1. Modeling the keyboard 2. Fiit’s law parameter estimation: r-squared = 0.709 3. Average typing time of 1000 most frequent words: 0.99 4. Zipf’s law parameter estimation & average typing time of 1000 most frequent words: 0.71 import matplotlib.pyplot as plt import math import numpy numpy.set_printoptions(precision=2) import scipy.stats as stats import statsmodels.api as sm from statsmodels.graphics.regressionplots import abline_plot import seaborn as sns 1. Keyboard modeling # Define keyboard line1 = 'qwertyuiop' line2 = 'asdfghjkl' line3 = 'zxcvbnm' # Define a keyboard as a list of keys.
10 minutes read
Convert Browser Requests to Python
Scraping dynamic content these days is bit difficult as there are wide variety of authentication mechanisms and web server needs correct headers, session, cookies to authenticate the request. If we need to quickly scrape content just for once, implementing authenticationis an overhead. Instead, we can manually login to the website, capture an authenticated request and use it for scraping other pages by changing url/form parameters.
curl 'https://www.glassdoor.com/member/home/index.htm' -H 'User-Agent: Mozilla/5.0 (X11; Linux x86_64; rv:99.
2 minutes read
Lets Clone the Voice of Priyanka Chopra Jonas
I had decided to get my email reminders using any celebrity’s voice in my previous post Alexa AI for reminding important emails and reminders. Here is a small step towards it :D
If you don’t know how Priyanka Chopra sounds like, here is a real sample Sample synthesized voice 1 Sample synthesized voice 2 Sample synthesized voice 3 Real voice of Amitabh Bachchan Sample synthesized voice for Amitabh Bachchan This one is more robotic.
2 minutes read
Alexa AI for reminding important emails and reminders
Motivation :- It was the third time I missed reading my email and picking up shifts for my oncampus job. I did try creating labels and filtering them but that didn’t show any progress in improvement. It’s really stressful when I get the notification that something needs a response from me right away. I had to make sure that I was not missing this next time. It is then when I decided I need to build a system to process and remind me this.
3 minutes read
Pca VS AutoEncoders
PCA import numpy as np import sklearn import matplotlib.pyplot as plt from sklearn.decomposition import PCA from sklearn.preprocessing import StandardScaler from sklearn.preprocessing import MinMaxScaler from tensorflow.keras.datasets import fashion_mnist import seaborn as sns import os import gzip import sys # The number of components for pca N_COMP = 100 #@param {type:"integer"} #Load data: (X_train, y_train), (X_test, y_test) = fashion_mnist.load_data() #Design matrix print('Design matrix size: {}'.format(X_train.shape)) Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/train-labels-idx1-ubyte.gz 32768/29515 [=================================] - 0s 0us/step 40960/29515 [=========================================] - 0s 0us/step Downloading data from https://storage.
5 minutes read
关于我
g1eny0ung 的 ❤️ 博客
记录一些 🌈 生活上，技术上的事
一名大四学生
马上（已经）毕业于 🏫 大连东软信息学院
职业是前端工程师
业余时间会做开源和 Apple App (OSX & iOS)
主要的技术栈是：
- JavaScript & TypeScript
- React.js
- Electron
- Rust
写着玩（写过）：
- Java & Clojure & CLJS
- OCaml & Reason & ReScript
- Dart & Swift
目前在 PingCAP 工作
– 2020 年 09 月 09 日更新
我的一些开源项目
- Petal 🌺 ➡️ 豆瓣 FM 桌面版
- hugo-theme-dream 🌱 ➡️ HUGO 的博客主题，当然，也是你现在看到的博客主题
- Alfred-Colors-workflow ➡️ Alfred 插件：CSS 颜色格式转换 hex <=> rgb <=> hsl
- github-colorful-contributions-graph ➡️ 改变 GitHub 贡献面板颜色的 Chrome 插件
- day.dart ➡️ ⏰ Day.js in dart.
其他
如果你喜欢我的开源项目或者它们可以给你带来帮助，可以赏一杯咖啡 ☕ 给我。~
If you like my open source projects or they can help you. You can buy me a coffee ☕.~
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最好附加一下信息或者留言，方便我可以将捐助记录 📝 下来，十分感谢 🙏。
It is better to attach some information or leave a message so that I can record the donation 📝, thank you very much 🙏.