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Improving the Aftermath Management of an Earthquake

Improving the Aftermath Management of an Earthquake | Omdena
Omdena | Building AI Solutions for Real-World Problems

Happy Valentine's Day from MATLAB ❤️ Code ⬇️

MathWorks on LinkedIn: Happy Valentine's Day from MATLAB ❤️ Code ⬇️ [y,x,z] = ndgrid(linspace | 98 comments
linkedin

50+ Statistics Interview Questions and Answers for Data Scientists for 2021

50+ Statistics Interview Questions and Answers for Data Scientists for 2022
Medium

DIY- Multi-Level Dendrogram

Siddharth Pawar on LinkedIn: #vismydata #vismydata #tableau
linkedin

How to use ML to perform RF modulation recognition?

James Heaton on LinkedIn: Xilinx/Vitis-Tutorials
linkedin

Tools for building robust, state-of-the-art machine learning models

Tools for building robust, state-of-the-art machine learning models
The Data Exchange

English Audio Speech-to-Text Transcript with Hugging Face | Python NLP

Neural Re-rendering for Full-frame Video Stabilization

Hybrid Neural Fusion for Full-frame Video Stabilization

AI-ML Cheat Sheets

https://www.linkedin.com/feed/update/urn:li:activity:6765855868929089537/
www.linkedin.com

Q4 2020 Food Delivery & Rideshare Sales Report

Q4 2020 Food Delivery & Rideshare Sales Report
Medium

AI PAPER SUMMARY

AI Paper Summary Archives
MarkTechPost

Microservices Architecture at Netflix!

Srivathsan Vijayaraghavan on LinkedIn: Check out the Microservices Architecture at Netflix! 1. Client sends
linkedin

10 Awesome Data Science Courses to make you an Awesome Data Scientist

https://www.linkedin.com/feed/update/urn:li:activity:6765214718861938688/
www.linkedin.com

Yann LeCun’s Deep Learning Course

Arpit Singh on LinkedIn: #DataScience #ML #machinelearning | 20 comments
linkedin

Analyzing seasonality with Fourier transforms using Python & SciPy

Theophano Mitsa Ph.D. on LinkedIn: Analyzing seasonality with Fourier transforms using Python & SciPy
linkedin

An open-source text annotation tool for humans

Steve Nouri on LinkedIn: #innovation #artificialintelligence #machinelearning | 58 comments
linkedin

PORORO: Platform Of neuRal mOdels for natuRal language prOcessing

Vincent Boucher on LinkedIn: #MachineLearning #NaturalLanguageProcessing #NLP
linkedin

Indian Flag with Turtle using Python

This Republic day I tried to do something creative and made an Indian Flag with Turtle using Python. Turtle is a pre-installed Python library. It enables users to create pictures and shapes by providing them with a virtual canvas.
You can also refer to the YouTube video tutorial for better understanding: https://lnkd.in/dUrctgE

The Shiny AWS Book

The Shiny AWS Book
bizscienc

10 Most Stable Linux Distros In 2021

10 Most Stable Linux Distros In 2021
Analytics India Magazine

Python’s Pandas vs. R’s dplyr

Python’s Pandas vs. R’s dplyr – Which Is The Best Data Analysis Library | R-bloggers
R-bloggers

Top Ten Kaggle Notebooks For Data Science Enthusiasts In 2021

Top Ten Kaggle Notebooks For Data Science Enthusiasts In 2021
Analytics India Magazine

An R package to build your resume or CV

Ludovic BOCKEN, PhDs (c) on LinkedIn: jaredlander/resumer
linkedin

Applied Data Science: Free E-Book

Machine Learning India on LinkedIn: Applied Data Science: Free E-Book | 14 comments
linkedin

"The Data Engineering Cookbook" by Andreas Kretz!!

https://www.linkedin.com/posts/imarpit_the-data-engineering-cookbook-by-andreas-activity-6763295036466626560-4itW/
www.linkedin.com

Data Cleaning

uday kiran reddy kondreddy on LinkedIn: data cleaning
linkedin

Wind Forecast

Florian Roscheck on LinkedIn: flrs/caiso_wind_forecast
linkedin

Fundamentals of Python Programming

Arpit Singh on LinkedIn: Fundamentals of Python Programming by Richard Halterman | 17 comments
linkedin

Mistakes to avoid as a Data Scientist

Learn.MachineLearning on LinkedIn: mistakes to avoid | 11 comments
linkedin

Fake AI generated blog

MIT Technology Review on LinkedIn: A college kid created a fake, AI-generated blog. It reached #1 on | 16 comments
linkedin

ML Interview Questions

Arpit Singh on LinkedIn: 41 Essential Machine Learning Interview QnAs
linkedin

BudgetML

GitHub - ebhy/budgetml: Deploy a ML inference service on a budget in less than 10 lines of code.
GitHub
Hamza Tahir on LinkedIn: ebhy/budgetml
linkedin
A Comprehensive guide to Fine-tuning Deep Learning Models in Keras (Part II) | Felix Yu
Canada’s AI Corridor is Maturing: The Canadian AI Ecosystem in 2018 - jfgagne
jfgagne
Canadian AI Ecosystem 2018 - jfgagne
jfgagne
Why we switched from Flask to FastAPI for production machine learning
Medium
Steve Nouri on LinkedIn: #artificialintelligence #datascience #deeplearning | 40 comments
linkedin
A Flask API for serving scikit-learn models
Medium
Philip Vollet on LinkedIn: #nlp #neuralnetworks #knowledgegraphs
linkedin
Modeling Global and Local Node Contexts for Text Generation from...
arXiv.org
GitHub - UKPLab/kg2text: Modeling Global and Local Node Contexts for Text Generation from Knowledge Graphs (authors' implementation for the TACL20 paper)
GitHub
Steve Nouri on LinkedIn: #augmentedreality #technology #datascience | 108 comments
linkedin
Philip Vollet on LinkedIn: #GNN #machinelearning #deeplearning | 15 comments
linkedin
Ontario schools will now teach first graders financial literacy and coding to better prepare students for jobs of the future
CNN
Morphological Processing for தமிழ் — The Unsupervised Way
Medium
PyTorch
GitHub - ChoudharyChanchal/game_control
GitHub
R-CNN object detection with Keras, TensorFlow, and Deep Learning - PyImageSearch
PyImageSearch
https://medium.com/towards-artificial-intelligence/main-types-of-neural-networks-and-its-applications-tutorial-734480d7ec8e
medium.com
You Don’t Understand Neural Networks Until You Understand the Universal Approximation Theorem
Medium
1-Introduction to Time Series and Forecasting https://lnkd.in/gqZbe7p
2-Statistics and Analysis of Scientific Data https://lnkd.in/g-hbjWZ
3-Linear Algebra Done Right https://lnkd.in/gqCT-6g
4-Linear Algebra https://lnkd.in/gJSPXQd
6-Understanding Analysis https://lnkd.in/g_RXeVk
7-Understanding Statistics Using R https://lnkd.in/g27NnMy
8-An Introduction to Statistical Learning https://lnkd.in/gyjbQ-A
9-Statistical Learning from a Regression Perspective https://lnkd.in/g2gFWfi
11-Regression Modeling Strategies https://lnkd.in/gR3Mufh
12-A Modern Introduction to Probability and Statistics https://lnkd.in/gCgbX6m
13-The Python Workbook https://lnkd.in/gw4tAf7
14-Machine Learning in Medicine — a Complete Overview https://lnkd.in/g43uZiT
15-Introduction to Data Science https://lnkd.in/gSvtBCs
16-Applied Predictive Modeling https://lnkd.in/gcHus2e
    1.
    Data Science Process https://pos.li/2fki4i
    2.
    Data Visualization in Business https://pos.li/2fki4j
    3.
    Know Machine Learning Key Terminology https://pos.li/2fki4k
    4.
    Understand Machine Learning Implementation https://pos.li/2fki4l
    5.
    Machine Learning Applications on Marketing https://pos.li/2fki4m and Retail https://pos.li/2fki4f
Is Canada still in the lead in AI?
LinkedInEditors
TOP 10 SQL Concepts for Job Interview
    1.
    Aggregate Functions (SUM/AVG)
    2.
    Group By and Order By
    3.
    JOINs (Inner/Left/Right)
    4.
    Union and Union All
    5.
    Date and Time processing
    6.
    String processing
    7.
    Window Functions (Partition by)
    8.
    Subquery
    9.
    View and Index
    10.
    Common Table Expression (CTE)
TOP 10 Statistics Concepts for Job Interview
    1.
    Sampling
    2.
    Experiments (A/B tests)
    3.
    Descriptive Statistics
    4.
    p-value
    5.
    Probability Distributions
    6.
    t-test
    7.
    ANOVA
    8.
    Correlation
    9.
    Linear Regression
    10.
    Logistics Regression
TOP 10 Python Concepts for Job Interview
    1.
    Reading data from file/table
    2.
    Writing data to file/table
    3.
    Data Types
    4.
    Function
    5.
    Data Preprocessing (numpy/pandas)
    6.
    Data Visualisation (Matplotlib/seaborn/bokeh)
    7.
    Machine Learning (sklearn)
    8.
    Deep Learning (Tensorflow/Keras/PyTorch)
    9.
    Distributed Processing (PySpark)
    10.
    Functional and Object Oriented Programming
Certificate Program in Quantum Engineering and Technology
University of Chicago Professional Education
Royal Bank of Canada, Borealis AI partner with Red Hat, NVIDIA on new AI computing platform | BetaKit
BetaKit
GitHub - adityamhatre/GameCarControl-CV
GitHub
Car controller for games using OpenCV
Medium
Gallery — pydeck 0.6.1 documentation
GitHub - dheerajiiitv/T5-paraphrase-generation
GitHub
10 COOL GPT-3 DEMOS
MLT | MACHINE LEARNING TOKYO
Data Science Topics: CRISP – DM - Project Management Methodology Exploratory Data Analytics (EDA) / Descriptive Analytics Statistical Data Business Intelligence and Data Visualization Plots & Inferential Statistics Probability Distributions (Continuous & Discrete) Hypothesis Testing - The ‘4’ Must Know Hypothesis Tests Data Mining Supervised Learning – Linear Regression, OLS Predictive Modelling – Multiple Linear Regression Lasso and Ridge Regressions Logistic Regression – Binary Value Prediction, MLE Multinomial Regression Advanced Regression for Count Data Data Mining Unsupervised Learning - Clustering Data Mining Unsupervised Learning - Dimension Reduction (PCA) Data Mining Unsupervised Learning - Association Rules Recommendation Engine Network Analytics Machine Learning - k - NN Classifier Decision Tree & Random Forest Ensemble Techniques - Bagging and Boosting AdaBoost & Extreme Gradient Boosting Text Mining & Natural Language Processing (NLP) Machine Learning Classifier Technique - Naive Bayes Introduction to Perceptron, Multilayer Perceptron Building Blocks of Neural Network Deep Learning Black Box Technique - Neural Network Deep Learning Black Box Technique - SVM Survival Analytics Forecasting/Time Series – Model Driven Algorithms Forecasting/Time Series – Data Driven Algorithms
BLURB Leaderboard
Domain-Specific Language Model Pretraining for Biomedical Natural...
arXiv.org
Step-by-step guide to contributing on GitHub
Data School
GitHub - tiangolo/full-stack-fastapi-postgresql: Full stack, modern web application generator. Using FastAPI, PostgreSQL as database, Docker, automatic HTTPS and more.
GitHub
Launch Your Career in Data Science
EliteDataScience
Writer Identification Using Microblogging Texts for Social Media Forensics
arXiv.org
TinyML is giving hardware new life
TechCrunch
GitHub - goru001/inltk: Natural Language Toolkit for Indic Languages aims to provide out of the box support for various NLP tasks that an application developer might need
GitHub
Natural Language Toolkit for Indic Languages — iNLTK latest documentation
GitHub - naiveHobo/InvoiceNet: Deep neural network to extract intelligent information from invoice documents.
GitHub
Group Normalization
Committed towards better future
Aman Arora on LinkedIn: Group Normalization
linkedin
Generative Teaching Networks: Accelerating Neural Architecture Search by Learning to Generate Synthetic Training Data
Uber Engineering Blog
Getting Started in NLP/ML Research - Victor Zhong
GitHub - TDAmeritrade/stumpy: STUMPY is a powerful and scalable Python library for modern time series analysis
GitHub
STUMPY documentation — stumpy 1.9.2 documentation
STUMPY
Medium
GitHub - Farama-Foundation/PettingZoo: Gym for multi-agent reinforcement learning
GitHub
GitHub - jim-schwoebel/allie: 🤖 A machine learning framework for audio, text, image, video, or .CSV files (50+ featurizers and 15+ model trainers).
GitHub
Twitter icon
Machine Learning with Graphs, Leskovec
http://snap.stanford.edu/class/cs224w-videos-2019/
snap.stanford.edu
China has started a grand experiment in AI education. It could reshape how the world learns.
MIT Technology Review
1-The Elements of Statistical Learning https://lnkd.in/gd-PpCa
2-Introductory Time Series with R https://lnkd.in/gemsHzv
3-A Beginner’s Guide to R https://lnkd.in/gwQ6m_B
4-Data Structures and Algorithms with Python https://lnkd.in/g9_djwr
5-Introduction to Statistics and Data Analysis https://lnkd.in/gUUJMCj
6-Principles of Data Mining https://lnkd.in/gMgmc-P
7-Computer Vision https://lnkd.in/gftqxf9
8-Data Mining https://lnkd.in/gJ6iugA
9-Robotics, Vision and Control https://lnkd.in/gq-q9i5
10-Statistical Analysis and Data Display https://lnkd.in/grCNSYq
11-Statistics and Data Analysis for Financial Engineering https://lnkd.in/gRn8zWd
12-Stochastic Processes and Calculus https://lnkd.in/gnWaWW6
13Statistical Analysis of Clinical Data on a Pocket Calculator https://lnkd.in/gM7VCgG
14-Clinical Data Analysis on a Pocket Calculator https://lnkd.in/gvxBvg6
15-The Data Science Design Manual https://lnkd.in/gKxgaRD
16-An Introduction to Machine Learning https://lnkd.in/gykPC2B
On-device, Real-time Body Pose Tracking with MediaPipe BlazePose
Google AI Blog
Slideio: a new python library for reading medical images.
Medium
Keras documentation: CycleGAN
Text Generation with Bi-LSTM in PyTorch
Medium
Amazon's Machine Learning University is making its online courses available to the public
Amazon Science
The untold story of GPT-3 is the transformation of OpenAI
TechTalks
GitHub - HenriquesLab/ZeroCostDL4Mic: ZeroCostDL4Mic: A Google Colab based no-cost toolbox to explore Deep-Learning in Microscopy
GitHub
Home · HenriquesLab/ZeroCostDL4Mic Wiki
GitHub
ZeroCostDL4Mic: an open platform to use Deep-Learning in Microscopy
bioRxiv
Too many AI researchers think real-world problems are not relevant
MIT Technology Review
OCR with Keras, TensorFlow, and Deep Learning - PyImageSearch
PyImageSearch
The Laplace Transform: A Generalized Fourier Transform
Facebook and NYU use artificial intelligence to make MRI scans four times faster
The Verge
Microsoft leads $16M round into AI data science startup Pachyderm
SiliconANGLE
GitHub - abhimishra91/insight: Repository for Project Insight: NLP as a Service
GitHub
GitHub - DevashishPrasad/CascadeTabNet: This repository contains the code and implementation details of the CascadeTabNet paper "CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documents"
GitHub
CVPR2020 Workshop on Text and Documents in the Deep Learning Era
CVPR2020 Workshop on Text and Documents in the Deep Learning Era
Google Colaboratory
GitHub - linkedin/detext: DeText: A Deep Neural Text Understanding Framework for Ranking and Classification Tasks
GitHub
https://dl.acm.org/doi/10.1145/3331184.3331381
dl.acm.org
The Ultimate guide to AI, Data Science & Machine Learning, Articles, Cheatsheets and Tutorials ALL in one place
LinkedInEditors
https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.161.3556&rep=rep1&type=pdf
’Introduction to Statistics for Data Science, Exploratory Data Analysis in Python‘
Distributions
Probability Mass Functions
Cumulative distribution functions
Modeling distributions
Probability density functions
Relationships between variables
Estimation
Hypothesis testing
Linear least squares
Regression
Time series analysis
Survival analysis
Analytic methods
Credit: Allen B. Downey
Forward from the 'Deep Learning for Coders' Book
fastdotai
fastbook/01_intro.ipynb at master · fastai/fastbook
GitHub
GitHub - fastai/fastbook: The fastai book, published as Jupyter Notebooks
GitHub
XGBoost Tutorials:
https://lnkd.in/g3dSRxz 1-Introduction to Boosted Trees 2-Distributed XGBoost with AWS YARN 3-Distributed XGBoost with XGBoost4J-Spark 4-DART booster 5-Monotonic Constraints 6-Random Forests in XGBoost 7-Feature Interaction Constraints 8-Text Input Format of DMatrix 9-Notes on Parameter Tuning 10-Using XGBoost External Memory Version (beta)
XGBoost Algorithm | XGBoost In Machine Learning
Analytics Vidhya
CatBoost vs. Light GBM vs. XGBoost - KDnuggets
KDnuggets
GitHub - INF800/realtime-forex-api
GitHub
GitHub - DevashishPrasad/CascadeTabNet: This repository contains the code and implementation details of the CascadeTabNet paper "CascadeTabNet: An approach for end to end table detection and structure recognition from image-based documents"
GitHub
Last modified 8mo ago