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10-steps-to-become-a-data-scientist

📢 Ready to learn or review your knowledge! You will learn 10 skills as data scientist: 📚 Python, Machine Learning, Deep Learning, Data Cleaning, EDA, python packages such as Numpy, Pandas, Seaborn, Matplotlib, Plotly, Tensorfolw, Theano...., Linear Algebra, Big Data, Analysis Tools and solve some real problems such as predict house prices.

amazon-review-scraper

A python library to scrape data from amazon.com

amazon-sagemaker-examples

Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker

amazonsagemakercourse

SageMaker Course Material

an-introduction-to-statistical-learning

This repository contains the exercises and its solution contained in the book "An Introduction to Statistical Learning" in python.

aws-saa-c02-course

Personal notes for SAA-C02 test from: https://learn.cantrill.io

bert-as-service

Mapping a variable-length sentence to a fixed-length vector using BERT model

causalml

Uplift modeling and causal inference with machine learning algorithms

courseraml

I took Andrew Ng's Machine Learning course on Coursera and did the homework assigments... but, on my own in python because I love jupyter notebooks!

d2l-en

Interactive deep learning book with code, math, and discussions. Available in multi-frameworks. Adopted at 140 universities.

data-science-by-john-hopkins

data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

datasciencecoursera

Repository for last project in Data Science Specialization by John Hopkins University

datasharing

The Leek group guide to data sharing

deep-learning-coursera

Deep Learning Specialization by Andrew Ng on Coursera.

deep-learning-in-production

In this repository, I will share some useful notes and references about deploying deep learning-based models in production.

deeplearning.ai-summary

This repository contains my personal notes and summaries on DeepLearning.ai specialization courses. I've enjoyed every little bit of the course hope you enjoy my notes too.

dlwpt-code

Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.

dsnd_term1

Contains files related to content and project of DSND

emotion-recognition-using-speech

Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras

end-to-end-ml-projects

ensemble-bagging-boosting

examples

Example deep learning projects that use wandb's features.

fastbook

Draft of the fastai book

functional_intro_to_python

A functional, Data Science focused introduction to Python

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

home-credit-default-competition

Gradient boosting model for predicting credit default risk on Kaggle competition

image-classifier

Image classifier using Pytorch

image-classifier-

introduction_to_ml_with_python

Notebooks and code for the book "Introduction to Machine Learning with Python"