vikram687 Goto Github PK

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

📢 Ready to learn! you will learn 10 skills as data scientist:📚 Machine Learning, Deep Learning, Data Cleaning, EDA, Learn Python, Learn 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.

ai-for-beginners

12 Weeks, 24 Lessons, AI for All!

anomaly_detection

This is a times series anomaly detection algorithm, implemented in Python, for catching multiple anomalies. It uses a moving average with an extreme student deviate (ESD) test to detect anomalous points.

argo-workflows

Workflow engine for Kubernetes

assignments

AWS Assignments

attention-is-all-you-need-pytorch

Repo has PyTorch implementation "Attention is All you Need - Transformers" paper for Machine Translation from French queries to English.

autoencoders-for-anomaly-detection

awesome-cybersecurity-datasets

A curated list of amazingly awesome Cybersecurity datasets

awesome-ml-for-cybersecurity

:octocat: Machine Learning for Cyber Security

awesome-rl

Reinforcement learning resources curated

aws

This repository consists of useful links for study materials for those aspiring carrer in AWS

bap

Bayesian Analysis with Python (Second Edition)

cka-k8s

ckad-exercises

A set of exercises to prepare for Certified Kubernetes Application Developer exam by Cloud Native Computing Foundation

collinearity_finder_treater

competitive-data-science

Materials for "How to Win a Data Science Competition: Learn from Top Kagglers" course

customer_segmentation

Analysing the content of an E-commerce database that contains list of purchases. Based on the analysis, I develop a model that allows to anticipate the purchases that will be made by a new customer, during the following year from its first purchase.

data-science

My notes pertaining to python programming, data analysis and visualization

data-science-complete-tutorial

Notebooks to learn data science - Videos https://www.edyoda.com/course/1416

data-scientist-books

Data-Scientist-Books (Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Long Short Term Memory, Generative Adversarial Network, Time Series Forecasting, Probability and Statistics, and more.)

deep-learning-for-hackers

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis)

deep-learning-for-natural-language-processing

Source Code for 'Deep Learning for Natural Language Processing' by Palash Goyal, Sumit Pandey and Karan Jain

deep-learning-keras-tf-tutorial

Learn deep learning with tensorflow2.0, keras and python through this comprehensive deep learning tutorial series. Learn deep learning from scratch. Deep learning series for beginners. Tensorflow tutorials, tensorflow 2.0 tutorial. deep learning tutorial python.

deep-learning-machine-learning-stock

Deep Learning and Machine Learning stocks represent a promising long-term or short-term opportunity for investors and traders.

deep-learning-with-keras

Code repository for Deep Learning with Keras published by Packt

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

deep-reinforcement-learning-with-python

Deep Reinforcement Learning with Python, Second Edition, published by Packt

deeplearning

deploy-machine-learning-model

Dockerize and deploy machine learning model as REST API using Flask

deployment-heroku

Deployment Heroku