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Practical Full-Stack Machine Learning
| Date | Stars |
|---|---|
| 2026-07-31 | 707 |
| 2026-08-04 | 707 |
| 2026-08-06 | 707 |
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growth rate 0.00%/day
[](https://bindichen.medium.com/) [](https://github.com/BindiChen/machine-learning)
# Machine Learning
Practical Machine Learning topics for articles in my [Medium blog](https://bindichen.medium.com/)
#### Content
1. [General Setup](#general-setup)
1. [Data Analysis](#data-analysis)
* [Pandas](#pandas)
* [Applied Data Analysis and EDA](#applied-data-analysis-and-eda)
1. [Web scraping](#web-scraping)
1. [Data Visualization](#data-visualization)
1. [TensorFlow](#tensorflow)
1. [PyTorch](#pytorch)
1. [Scikit-Learn](#scikit-learn-and-general-machine-learning)
## General Setup
* [Create Virtual Environment using “virtualenv” and add it to Jupyter Notebook](https://towardsdatascience.com/create-virtual-environment-using-virtualenv-and-add-it-to-jupyter-notebook-6e1bf4e03415)
* [Create Virtual Environment using “conda” and add it to Jupyter Notebook](https://medium.com/analytics-vidhya/create-virtual-environment-using-conda-and-add-it-to-jupyter-notebook-d319a81dfd1)
* [7 ways to load external data into Google Colab](https://bindichen.medium.com/7-ways-to-load-external-data-into-google-colab-7ba73e7d5fc7)
## Data Analysis
### Pandas
* Reading & Writing data
* [4 tricks to parse date columns with Pandas `read_csv()`](https://towardsdatascience.com/4-tricks-you-should-know-to-parse-date-columns-with-pandas-read-csv-27355bb2ad0e) | [](data-analysis/012-parse-date-with-read_csv/parse-date-column-with-read_csv.ipynb)
* [Pandas `read_csv()` tricks you should know](https://medium.com/@bindiatwork/all-the-pandas-read-csv-you-should-know-to-speed-up-your-data-analysis-1e16fe1039f3) | [](data-analysis/006-pandas-read_csv/read_csv-tricks.ipynb)
* [All Pandas `read_html()` you should know for scraping data from HTML tables](https://bindichen.medium.com/all-pandas-read-html-you-should-know-for-scraping-data-from-html-tables-a3cbb5ce8274) | [](data-analysis/024-pandas-read_html/pandas-read_html.ipynb)
* [How to convert JSON into a Pandas DataFrame?](https://bindichen.medium.com/how-to-convert-json-into-a-pandas-dataframe-100b2ae1e0d8) | [](data-analysis/027-pandas-convert-json/pandas-convert-json.ipynb)
* [Pandas `json_normalize()` for flattening JSON](https://bindichen.medium.com/all-pandas-json-normalize-you-should-know-for-flattening-json-13eae1dfb7dd) | [](data-analysis/028-pandas-json_normalize/pandas-json_normalize.ipynb)
* Data Profiling
* [9 Pandas `value_counts()` tricks](https://towardsdatascience.com/9-pandas-value-counts-tricks-to-improve-your-data-analysis-7980a2b46536) | [](data-analysis/046-pandas-value_counts/pandas-value_counts.ipynb)
* [Getting more value from the Pandas `count()`](https://bindichen.medium.com/getting-more-value-from-the-pandas-count-3e45a62c7077) | [](data-analysis/043-pandas-count/pandas-count.ipynb)
* Data Preprocessing
* [What is One-Hot Encoding and how to use `get_dummies()`](https://towardsdatascience.com/what-is-one-hot-encoding-and-how-to-use-pandas-get-dummies-function-922eb9bd4970) | [](data-analysis/002-one-hot-encoding/one-hot-encoding.ipynb)
* [Working with missing values in Pandas](https://towardsdatascience.com/working-with-missing-vExcerpt of 21,883 characters
Read on GitHub
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:4fed294fc956a450, topic:deep-learning