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License: GNU General Public License v3.0

Jupyter Notebook 98.72% Python 1.26% Julia 0.02%
data-structures deep-q-learning dsa-algorithm github grokking-coding-interview hackerearth-solutions interview-preparation interview-questions julia kaggle-competition leetcode leetcode-python leetcode-solutions practice-programming project-euler-python-solutions python python3

self-development's Introduction




7+ Yrs. Total Experience | Pidilite Industries | Ex-Reliance Jio

Waving Hand Light Skin Tone Hello everyone, this is Debmalya Pramanik. I've completed my graduation majoring in Electrical and Electronics Engineering. I'm currently working at Reliance Jio Infocomm Ltd as Data Analytics (Manager) since October 2016, and have experience in Python, Machine Learning, SQL, Tableau, Spark with Python (PySpark), Hive, and Deep Learning methodologies like Recurring Neural Networks (RNN). I've also completed my M. Tech (3 Years) in Power Electronics and Electrical Drives from the Indian Institute of Technology (IIT-ISM), Dhanbad.

Face with Monocle Looking for Contributers/Collaborators to Work on an Open Source Python hobby Project. Project and Repositories is available under pOrgz-dev. Also, I am working in collaboration with VisualCrossing to create a python wrapper to easily fetch and manipulate weather data. If interested, feel free to send PRs! (Code available at ZenithClown/VisualCrossing)

Triangular Flag Language & Tools

# Language/Platforms Self Rating
CTRL + C & CTRL + V Fire FlameNerd Face
versionining/tracking Crossed FingersSmiling Face with Open Hands
learning Man Student

bash docker flask git hive jenkins kubernetes linux matlab mongodb mssql mysql pandas postgresql postman python pytorch scikit_learn seaborn sqlite tensorflow travisci

Keywords: data, science, analyst, data scientist, data analyst, machine learning, neural networks, deep learning, statistics, visualization, python, templates, flask, weather, rest api, jupyter notebook, analysis, modeling

Pushpin Pinned GitHub Gists

The section features some of my defined gists used throughout my projects. The related repositories have also been added as git submodule, generally called using PYTHONPATH in the system. For a detailed guide of environment setup check โš  configurations (my gitlab/ZenithClown account) for more details. The pinned repositories are categorized into the following sections:

  • Robot AI/ML: Repositories designed for achieving some AI/ML related tasks. For example, these repositories are designed to perform feature engineering, model creation, optimization, etc.
  • Crystal Ball Story Telling: A set of curated repositories designed for generating graphs, charts and images for various storytelling/business analysis/statistical understanding purposes.
  • Thinking Face Other Gist(s): Other important gists that do not belong to any of the above defined categories.
Robot AI/ML Crystal Ball Story Telling Thinking Face Other Gists
Alarm ClockZenithClown/ts_featuring
Create a set of training data
(x_train, y_train) for time series model
training and feature development.
pythonโญ 1, ๐Ÿ”€ 0
ZenithClown/pandas_
a set of functions that extends from pandas
to reduce code duplicacy
pythonโญ 0, ๐Ÿ”€ 0
ZenithClown/scaler
a custom built object-oriented
approach to scale a data series
pythonโญ 0, ๐Ÿ”€ 0
Bar ChartZenithClown/corr_visualization
Visualize correlation heatmap.
pythonโญ 1, ๐Ÿ”€ 0
Alarm ClockZenithClown/dt_utils
An extension of datetime module to
provide additional functionalities.
pythonโญ 0, ๐Ÿ”€ 0
ZenithClown/geometry
a set of utility functions
for manipulating
shapely.geometry objects
pythonโญ 0, ๐Ÿ”€ 0

self-development's People

Contributors

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Watchers

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Forkers

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self-development's Issues

[Bug]: [Enhancement]: Structuring Project

Contact Details

No response

What happened?

The project and subdirectories need a significant restructuring, as the codes, files, and information are haphazardly available. The following suggestions are to be addressed:

  • create directories separated by topics,
  • put all template/boilerplate files separated by topics, and
  • reduce folder/directory name (longpath) issue and inconsistency.

Python Version

3.9.12 (default)

What type of operating system are you using?

Windows 10, Linux (debian/ubuntu/mint/etc.)

Relevant log output

No response

Code of Conduct

  • I agree to follow this project's Code of Conduct

[Enhancement]:

Contact Details

No response

Explain the Feature/Enhancement?

The LeetCode directory progress bar can be automated using a python script:

Code of Conduct

  • I agree to follow this project's Code of Conduct

[Enhancement]: Creating a Reference Table for LeetCode Daily Challenges

Contact Details

No response

Explain the Feature/Enhancement?

LeetCode provides daily challenges. Use a section to showcase all the solved problems featured in this challenge. In addition, also add comments and keywords (i.e. SEO) to increase view traffics.

  • Create a <details> ... </details> Tagging Template
  • Create a year followed by a month selection to keep the view at a minimum level.
  • Create a redirect URL schema and provide keywords.
  • #15

Code of Conduct

  • I agree to follow this project's Code of Conduct

[Bug]: Filling NaN Values

Contact Details

No response

What happened?

Null values are not automatically populated using df.fillna({}, inplace = True) command. [commit: 949cc1d] but works when using df = df.fillna({}) command.

Python Version

3.9.12 (default)

What type of operating system are you using?

Windows 10

Relevant log output

No response

Code of Conduct

  • I agree to follow this project's Code of Conduct

[Bug]: Wrong Implementation of Finding

Contact Details

No response

What happened?

The method .find() reports all elements to be present in the Singly Linked Lists even when not present.
image

  • Check the .find() method with a mock-up code.
  • Check .next() and .head() method implementation.

Python Version

3.9.12 (default)

What type of operating system are you using?

Windows 10

Relevant log output

llist = SinglyLinkedList()
llist.append(10) # add a new element

# find the new element in the linked list
llist.find("not present") # returns True

Code of Conduct

  • I agree to follow this project's Code of Conduct

Statistical Information is not Displayed on Type Casting

Overview

A type casting function is developed (based on this link) to reduce the memory usage of a dataframe. However, using the function the statistical information is missing when using pd.describe() feature.

Steps to Reproduce

  1. Use the pd.describe() method w/o any modifications, results in:
    image
  2. Now, define/import reduce_mem_usage
  3. Using the same function, the output is changed as:
    image

Expected Behavior

Should be able to use all statistical features.

Actual Behavior

Direct describe function is not working, but using native numpy functions (like np.quantile(trn_data["f_00"], 0.95)) works.

Context

Python Version : 3.9
Operating System : Windows 10 (Version: 21H2, OS Build: 19044.1682)

[Enhancement]: Require Repository Description & Documentations

Contact Details

No response

Explain the Feature/Enhancement?

As under community guidelines, the description needs to be added to the repository.

Related Tasks List

A list of additional tasks that are tracked and needs to be โœ… completed before closing this issue are mentioned below. (NOTE: these tasks may not be in a specific order, and is added when required/raised).

Code of Conduct

  • I agree to follow this project's Code of Conduct

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