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Showing posts from July, 2023

What is Streamlit? Web app maker for Engineers

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   What is Streamlit?  Web app maker for Engineers Introduction After getting into Python for a while, I have done a few projects, including web bots, machine learning, deep learning, etc. Often times my project requires some kind of interface to control the project program or send data to the program (etc: picture). This could be done by PyGame, the terminal, or making a web application. But getting familiar with those skills takes a lot of time, and will be time-consuming to build these interfaces for one project -- that is until I found Streamlit. I want to share this incredible Python web-building tool and show you how I used it to create my first deployed web application. In fact, this web application is just a showcase of basic streamlit functionalities.  - You can look at my website here:  myfirstappapp-rmv48wgigs.streamlit.app - You can find the code here:  lambo131/my_first_streamlit_app (github.com) - You can find the streamlit get started tutoria...

Lang Chain

Explore these: - OpenAI plugins - Agent types - OpenAI China personel payment OpenAI China personel payment Register for vitual/crypto credit card - choice: OneKey Notes while doing up openai payment - Use VPN(US region) - Choose tax-free area when filling address 

Image classification with CNN

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 Image classification with CNN What is Convolution Neural Network(CNN)? CNN is a type of supervised deep-learning algorithm that uses matrix feature extraction along with a densely connected network for classification tasks. CNN is most popular for image classification, but it can also be used for audio, signal, and time series classification. How does CNN work CNN is composed of a feature extraction part and a classification part.  Features are extracted with matrix operations. Basically, a filter matrix moves across the dataset. When it is overlapping with data that has high similarity as the filter, it will output a number close to 1 for that position and 0 vice versa. This is done by multiplying each of the filter values with a corresponding value of the dataset and dividing their sum by the number of values of the filter. Then, a ReLu function is used to non-linearize the data. There are options for feature extraction such as padding, stride, and filter window. Padding ad...

Learning... Machine Learning

Introduction At the time of writing this post, I have just a little understanding in machine learning. I did some basic ANN with Keras and learned how to use a little bit of pandas.  This post is a planning and resource page for my machine learning journey and projects.  Here is a list of things I want to explore in the field of ML Web scrapping for ML Image classification (with CNNs) Reinforcement learning, customize environments (with DQN) OpenAI API Stream lit web tool scripting Some useful tools to learn: stream lit: Create web apps very quickly. This is useful for prototyping ideas and developing projects  Learning resources and project tutorials for each of these topics are detailed below. I will have separate posts when I explore each of these topics. Yes, this is the "planning stage".  Expectations - Spend a minimum of 5 hours every week - Improve the learning process - Improve expression ability, explain concepts as I learn Some good tutors in these areas co...

The Journey begins

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  The Journey Begins Brief introduction Hi, My name is Lambo Qin, and I am starting a blog. It may seem a bit old-fashioned. True, but I think it will be a great choice to record the things I have done and document my learning process. Anyway, this blog will be about me learning Computer/Electronics Engineering and doing projects. Like machine learning, computer vision, and robotics. That's it for my first post, bye. PS(to me):   keep it up!