A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep

James Le

Last update: Jan 2, 2023

Overview

Here are the sections:

Data Science Cheatsheets
Data Science EBooks
Data Science Question Bank
Data Science Case Studies
Data Science Portfolio
Data Journalism Portfolio
Downloadable Cheatsheets

Data Science Cheatsheets

This section contains cheatsheets of basic concepts in data science that will be asked in interviews:

Data Science EBooks

This section contains books that I have read about data science and machine learning:

Data Science Question Bank

This section contains sample questions that were asked in actual data science interviews:

Data Science Case Studies

This section contains case study questions that concern designing machine learning systems to solve practical problems.

Data Science Portfolio

This section contains portfolio of data science projects completed by me for academic, self learning, and hobby purposes.

For a more visually pleasant experience for browsing the portfolio, check out jameskle.com/data-portfolio

Recommendation Systems
- Transfer Rec: My ongoing research work that intersects deep learning and recommendation systems.
- Movie Recommendation: Designed 4 different models that recommend items on the MovieLens dataset.
Tools: PyTorch, TensorBoard, Keras, Pandas, NumPy, SciPy, Matplotlib, Seaborn, Scikit-Learn, Surprise, Wordcloud
Machine Learning
- Trip Optimizer: Used XGBoost and evolutionary algorithms to optimize the travel time for taxi vehicles in New York City.
- Instacart Market Basket Analysis: Tackled the Instacart Market Basket Analysis challenge to predict which products will be in a user's next order.
Tools: Pandas, NumPy, Matplotlib, XGBoost, Geopy, Scikit-Learn
Computer Vision
- Fashion Recommendation: Built a ResNet-based model that classifies and recommends fashion images in the DeepFashion database based on semantic similarity.
- Fashion Classification: Developed 4 different Convolutional Neural Networks that classify images in the Fashion MNIST dataset.
- Dog Breed Classification: Designed a Convolutional Neural Network that identifies dog breed.
- Road Segmentation: Implemented a Fully-Convolutional Network for semantic segmentation task in the Kitty Road Dataset.
Tools: TensorFlow, Keras, Pandas, NumPy, Matplotlib, Scikit-Learn, TensorBoard
Natural Language Processing
- Classifying Tweets with Weights & Biases: Developed 3 different neural network models that classify tweets on a crowdsourced dataset in Figure Eight.
Data Analysis and Visualization
- World Cup 2018 Team Analysis: Analysis and visualization of the FIFA 18 dataset to predict the best possible international squad lineups for 10 teams at the 2018 World Cup in Russia.
- Spotify Artists Analysis: Analysis and visualization of musical styles from 50 different artists with a wide range of genres on Spotify.
Tools: Pandas, NumPy, Matplotlib, Rspotify, httr, dplyr, tidyr, radarchart, ggplot2

Data Journalism Portfolio

This section contains portfolio of data journalism articles completed by me for freelance clients and self-learning purposes.

For a more visually pleasant experience for browsing the portfolio, check out jameskle.com/data-journalism

Downloadable Cheatsheets

These PDF cheatsheets come from BecomingHuman.AI.

1 - Neural Network Basics

2 - Neural Network Graphs

3 - Machine Learning with Emojis

4 - Scikit-Learn With Python

5 - Python Basics

6 - NumPy Basics

7 - Pandas Basics

8 - Data Wrangling With Pandas

9 - SciPy Linear Algebra

10 - Matplotlib Basics

11 - Keras

12 - Big-O

Code for our SIGIR 2022 accepted paper : P3 Ranker: Mitigating the Gaps between Pre-training and Ranking Fine-tuning with Prompt-based Learning and Pre-finetuning

P3 Ranker Implementation for our SIGIR2022 accepted paper: P3 Ranker: Mitigating the Gaps between Pre-training and Ranking Fine-tuning with Prompt-bas

14 Jan 4, 2023

🏆 A ranked list of awesome python developer tools and libraries. Updated weekly.

Best-of Python Developer Tools 🏆 A ranked list of awesome python developer tools and libraries. Updated weekly. This curated list contains 250 awesom

646 Jan 7, 2023

ReStructuredText and Sphinx bridge to Doxygen

Breathe Packagers: PGP signing key changes for Breathe = v4.23.0. https://github.com/michaeljones/breathe/issues/591 This is an extension to reStruct

643 Dec 31, 2022

Watch a Sphinx directory and rebuild the documentation when a change is detected. Also includes a livereload enabled web server.

sphinx-autobuild Rebuild Sphinx documentation on changes, with live-reload in the browser. Installation sphinx-autobuild is available on PyPI. It can

440 Jan 6, 2023

An MkDocs plugin that simplifies configuring page titles and their order

MkDocs Awesome Pages Plugin An MkDocs plugin that simplifies configuring page titles and their order The awesome-pages plugin allows you to customize

282 Dec 28, 2022

Flask-Rebar combines flask, marshmallow, and swagger for robust REST services.

Flask-Rebar Flask-Rebar combines flask, marshmallow, and swagger for robust REST services. Features Request and Response Validation - Flask-Rebar reli

223 Dec 19, 2022

NetBox plugin that stores configuration diffs and checks templates compliance

Config Officer - NetBox plugin NetBox plugin that deals with Cisco device configuration (collects running config from Cisco devices, indicates config

77 Dec 21, 2022

API spec validator and OpenAPI document generator for Python web frameworks.

249 Dec 22, 2022

Documentation generator for C++ based on Doxygen and mosra/m.css.

mosra/m.css is a Doxygen-based documentation generator that significantly improves on Doxygen's default output by controlling some of Doxygen's more unruly options, supplying it's own slick HTML+CSS generation and adding a fantastic live search feature.

109 Dec 7, 2022

Comments

Bump numpy from 1.11.1 to 1.21.0 in /EBooks/Python-Data-Science-Handbook
Bumps numpy from 1.11.1 to 1.21.0.

Release notes

Sourced from numpy's releases.

v1.21.0

NumPy 1.21.0 Release Notes

The NumPy 1.21.0 release highlights are

continued SIMD work covering more functions and platforms,

initial work on the new dtype infrastructure and casting,

universal2 wheels for Python 3.8 and Python 3.9 on Mac,

improved documentation,

improved annotations,

new PCG64DXSM bitgenerator for random numbers.

In addition there are the usual large number of bug fixes and other improvements.

The Python versions supported for this release are 3.7-3.9. Official support for Python 3.10 will be added when it is released.

:warning: Warning: there are unresolved problems compiling NumPy 1.21.0 with gcc-11.1 .

Optimization level -O3 results in many wrong warnings when running the tests.

On some hardware NumPy will hang in an infinite loop.

New functions

Add PCG64DXSM BitGenerator

Uses of the PCG64 BitGenerator in a massively-parallel context have been shown to have statistical weaknesses that were not apparent at the first release in numpy 1.17. Most users will never observe this weakness and are safe to continue to use PCG64. We have introduced a new PCG64DXSM BitGenerator that will eventually become the new default BitGenerator implementation used by default_rng in future releases. PCG64DXSM solves the statistical weakness while preserving the performance and the features of PCG64.

See upgrading-pcg64 for more details.

(gh-18906)

Expired deprecations

The shape argument numpy.unravel_index cannot be passed as dims keyword argument anymore. (Was deprecated in NumPy 1.16.)

... (truncated)

Commits

b235f9e Merge pull request #19283 from charris/prepare-1.21.0-release

34aebc2 MAINT: Update 1.21.0-notes.rst

493b64b MAINT: Update 1.21.0-changelog.rst

07d7e72 MAINT: Remove accidentally created directory.

032fca5 Merge pull request #19280 from charris/backport-19277

7d25b81 BUG: Fix refcount leak in ResultType

fa5754e BUG: Add missing DECREF in new path

61127bb Merge pull request #19268 from charris/backport-19264

143d45f Merge pull request #19269 from charris/backport-19228

d80e473 BUG: Removed typing for == and != in dtypes

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dependencies
opened by dependabot[bot] 1
Bump pillow from 3.4.2 to 6.2.0 in /EBooks/Python-Data-Science-Handbook
Bumps pillow from 3.4.2 to 6.2.0.

Release notes

Sourced from pillow's releases.

6.2.0

https://pillow.readthedocs.io/en/stable/releasenotes/6.2.0.html

6.1.0

https://pillow.readthedocs.io/en/stable/releasenotes/6.1.0.html

6.0.0

No release notes provided.

5.4.1

No release notes provided.

5.4.0

No release notes provided.

5.3.0

No release notes provided.

5.2.0

No release notes provided.

5.1.0

No release notes provided.

5.0.0

No release notes provided.

4.3.0

No release notes provided.

4.2.1

No release notes provided.

4.2.0

No release notes provided.

4.1.1

No release notes provided.

4.1.0

No release notes provided.

4.0.0 tag had a typo in the version in setup.py, hence 4.0.0a

Changelog

Sourced from pillow's changelog.

6.2.0 (2019-10-01)

Catch buffer overruns #4104 [radarhere]

Initialize rows_per_strip when RowsPerStrip tag is missing #4034 [cgohlke, radarhere]

Raise error if TIFF dimension is a string #4103 [radarhere]

Added decompression bomb checks #4102 [radarhere]

Fix ImageGrab.grab DPI scaling on Windows 10 version 1607+ #4000 [nulano, radarhere]

Corrected negative seeks #4101 [radarhere]

Added argument to capture all screens on Windows #3950 [nulano, radarhere]

Updated warning to specify when Image.frombuffer defaults will change #4086 [radarhere]

Changed WindowsViewer format to PNG #4080 [radarhere]

Use TIFF orientation #4063 [radarhere]

Raise the same error if a truncated image is loaded a second time #3965 [radarhere]

Lazily use ImageFileDirectory_v1 values from Exif #4031 [radarhere]

Improved HSV conversion #4004 [radarhere]

Added text stroking #3978 [radarhere, hugovk]

No more deprecated bdist_wininst .exe installers #4029 [hugovk]

Do not allow floodfill to extend into negative coordinates #4017 [radarhere]

... (truncated)

Commits

8a30d13 Updated CHANGES.rst [ci skip]

75602d1 6.2.0 version bump

4756af9 Updated CHANGES.rst [ci skip]

cc16025 Merge pull request #4104 from radarhere/overrun

fb84701 Merge pull request #4034 from cgohlke/patch-1

b9693a5 Merge pull request #4103 from radarhere/dimension

f228d0c Merge pull request #4102 from radarhere/decompression

aaf2c42 Merge pull request #4000 from nulano/dpi_fix

b36c1bc Merge pull request #4101 from radarhere/negative_seek

9a977b9 Raise error if dimension is a string

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dependencies
opened by dependabot[bot] 1
Bump numpy from 1.11.1 to 1.22.0 in /EBooks/Python-Data-Science-Handbook
Bumps numpy from 1.11.1 to 1.22.0.

Release notes

Sourced from numpy's releases.

v1.22.0

NumPy 1.22.0 Release Notes

NumPy 1.22.0 is a big release featuring the work of 153 contributors spread over 609 pull requests. There have been many improvements, highlights are:

Annotations of the main namespace are essentially complete. Upstream is a moving target, so there will likely be further improvements, but the major work is done. This is probably the most user visible enhancement in this release.

A preliminary version of the proposed Array-API is provided. This is a step in creating a standard collection of functions that can be used across application such as CuPy and JAX.

NumPy now has a DLPack backend. DLPack provides a common interchange format for array (tensor) data.

New methods for quantile, percentile, and related functions. The new methods provide a complete set of the methods commonly found in the literature.

A new configurable allocator for use by downstream projects.

These are in addition to the ongoing work to provide SIMD support for commonly used functions, improvements to F2PY, and better documentation.

The Python versions supported in this release are 3.8-3.10, Python 3.7 has been dropped. Note that 32 bit wheels are only provided for Python 3.8 and 3.9 on Windows, all other wheels are 64 bits on account of Ubuntu, Fedora, and other Linux distributions dropping 32 bit support. All 64 bit wheels are also linked with 64 bit integer OpenBLAS, which should fix the occasional problems encountered by folks using truly huge arrays.

Expired deprecations

Deprecated numeric style dtype strings have been removed

Using the strings "Bytes0", "Datetime64", "Str0", "Uint32", and "Uint64" as a dtype will now raise a TypeError.

(gh-19539)

Expired deprecations for loads, ndfromtxt, and mafromtxt in npyio

numpy.loads was deprecated in v1.15, with the recommendation that users use pickle.loads instead. ndfromtxt and mafromtxt were both deprecated in v1.17 - users should use numpy.genfromtxt instead with the appropriate value for the usemask parameter.

(gh-19615)

... (truncated)

Commits

4adc87d Merge pull request #20685 from charris/prepare-for-1.22.0-release

fd66547 REL: Prepare for the NumPy 1.22.0 release.

125304b wip

c283859 Merge pull request #20682 from charris/backport-20416

5399c03 Merge pull request #20681 from charris/backport-20954

f9c45f8 Merge pull request #20680 from charris/backport-20663

794b36f Update armccompiler.py

d93b14e Update test_public_api.py

7662c07 Update init.py

311ab52 Update armccompiler.py

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dependencies
opened by dependabot[bot] 0

Owner

James Le

Data Journalist 📝 -> Data Scientist 📊 -> Machine Learning Researcher 🔍 -> Data Advocate 🤝

GitHub https://medium.com/cracking-the-data-science-interview

Grokking the Object Oriented Design Interview

2.6k Jan 8, 2023

CoderByte | Practice, Tutorials & Interview Preparation Solutions|

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Version bêta d'un système pour suivre les prix des livres chez Books to Scrape,

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Swagger UI is a collection of HTML, JavaScript, and CSS assets that dynamically generate beautiful documentation from a Swagger-compliant API.

Introduction Swagger UI allows anyone — be it your development team or your end consumers — to visualize and interact with the API’s resources without

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A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep

Related tags

Overview

Data Science Cheatsheets

Data Science EBooks

Data Science Question Bank

Data Science Case Studies

Data Science Portfolio

Recommendation Systems

Machine Learning

Computer Vision

Natural Language Processing

Data Analysis and Visualization

Data Journalism Portfolio

Statistics

Machine Learning

Deep Learning

Downloadable Cheatsheets

1 - Neural Network Basics

2 - Neural Network Graphs

3 - Machine Learning with Emojis

4 - Scikit-Learn With Python

5 - Python Basics

6 - NumPy Basics

7 - Pandas Basics

8 - Data Wrangling With Pandas

9 - SciPy Linear Algebra

10 - Matplotlib Basics

11 - Keras

12 - Big-O

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Comments

Bump numpy from 1.11.1 to 1.21.0 in /EBooks/Python-Data-Science-Handbook

v1.21.0

NumPy 1.21.0 Release Notes

New functions

Add PCG64DXSM BitGenerator

Expired deprecations

Bump pillow from 3.4.2 to 6.2.0 in /EBooks/Python-Data-Science-Handbook

6.2.0

6.1.0

6.0.0

5.4.1

5.4.0

5.3.0

5.2.0

5.1.0

5.0.0

4.3.0

4.2.1

4.2.0

4.1.1

4.1.0

6.2.0 (2019-10-01)

Bump numpy from 1.11.1 to 1.22.0 in /EBooks/Python-Data-Science-Handbook

v1.22.0

NumPy 1.22.0 Release Notes

Expired deprecations

Deprecated numeric style dtype strings have been removed

Expired deprecations for loads, ndfromtxt, and mafromtxt in npyio

Owner

James Le

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CoderByte | Practice, Tutorials & Interview Preparation Solutions|

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Swagger UI is a collection of HTML, JavaScript, and CSS assets that dynamically generate beautiful documentation from a Swagger-compliant API.

The tutorial is a collection of many other resources and my own notes

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Expired deprecations for `loads`, `ndfromtxt`, and `mafromtxt` in npyio