Stephen-Rimac / Python For Data Scientists
Deliverable: This Jupyter notebook will help aspiring data scientists learn and practice the necessary python code needed for many data science projects.
Stars: ✭ 86
Labels
Projects that are alternatives of or similar to Python For Data Scientists
Convgp
Convolutional Gaussian processes based on GPflow.
Stars: ✭ 85 (-1.16%)
Mutual labels: jupyter-notebook
Sphinx Book Theme
A lightweight book theme built off of the pydata sphinx theme
Stars: ✭ 86 (+0%)
Mutual labels: jupyter-notebook
Sagemaker Ml Workflow With Apache Airflow
This repository shows a sample example to build, manage and orchestrate Machine Learning workflows using Amazon Sagemaker and Apache Airflow.
Stars: ✭ 86 (+0%)
Mutual labels: jupyter-notebook
Aureliengeron
“Hands-On Machine Learning with Scikit-Learn and TensorFlow” Excerpt From: Aurélien Géron. “Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems.” iBooks.
Stars: ✭ 85 (-1.16%)
Mutual labels: jupyter-notebook
Breast Cancer Classification
Breast Cancer Classification using CNN and transfer learning
Stars: ✭ 86 (+0%)
Mutual labels: jupyter-notebook
Local light field synthesis
Local Light Field Synthesis (Pratul P. Srinivasan, Tongzhou Wang, Ashwin Sreelal, Ravi Ramamoorthi, Ren Ng ICCV 2017)
Stars: ✭ 86 (+0%)
Mutual labels: jupyter-notebook
Kaggle Competitions
There are plenty of courses and tutorials that can help you learn machine learning from scratch but here in GitHub, I want to solve some Kaggle competitions as a comprehensive workflow with python packages. After reading, you can use this workflow to solve other real problems and use it as a template.
Stars: ✭ 86 (+0%)
Mutual labels: jupyter-notebook
Training Material
A collection of code examples as well as presentations for training purposes
Stars: ✭ 85 (-1.16%)
Mutual labels: jupyter-notebook
Network science meets deep learning
Designing Deep neural network architectures using topologies from the world of Complex Networks/network Science
Stars: ✭ 86 (+0%)
Mutual labels: jupyter-notebook
Knet.jl
Koç University deep learning framework.
Stars: ✭ 1,260 (+1365.12%)
Mutual labels: jupyter-notebook
100 Plus Python Programming Exercises Extended
100+ python programming exercise problem discussed ,explained and solved in different ways
Stars: ✭ 1,250 (+1353.49%)
Mutual labels: jupyter-notebook
Wotan
Automagically remove trends from time-series data
Stars: ✭ 86 (+0%)
Mutual labels: jupyter-notebook
Introdatasci
Course materials for: Introduction to Data Science and Programming
Stars: ✭ 86 (+0%)
Mutual labels: jupyter-notebook
Book Mlearn Gyomu
Book sample (AI Machine-learning Deep-learning)
Stars: ✭ 84 (-2.33%)
Mutual labels: jupyter-notebook
Read me
This Jupyter notebook will help aspiring data scientists learn and practice the necessary python code needed for many data science projects.
Instructions
- You can insert "scratch" code cells using Insert > Insert Cell Below/Above in the toolbar.
- Remember, to run a cell, you can click into it anywhere and press
Shift + Enter
. - The
Green
text in the code cell, usually preceded by a pound sign (hashtag or #) is a comment and is not executed. - A
project_files
folder accompanies the download from GitHub. It contains important data needed for some of the analyses in the notebook.
Table of Contents
- Python Basics
- Data Structures
- Flow and Functions
- NumPy
- Pandas
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].