​François Chollet: Keras, Deep Learning, and the Progress of AI | Artificial Intelligence Podcast

🔗 François Chollet: Keras, Deep Learning, and the Progress of AI | Artificial Intelligence Podcast
François Chollet is the creator of Keras, which is an open source deep learning library that is designed to enable fast, user-friendly experimentation with deep neural networks. It serves as an interface to several deep learning libraries, most popular of which is TensorFlow, and it was integrated into TensorFlow main codebase a while back. Aside from creating an exceptionally useful and popular library, François is also a world-class AI researcher and software engineer at Google, and is definitely an outsp

​Data Visualization Tips (Power BI) — Convert Categorical Variables to Dummy Variables

🔗 Data Visualization Tips (Power BI) — Convert Categorical Variables to Dummy Variables
Skills on data preprocessing with PowerBI

​Teaching AI to plan using language in a new open-source strategy game

https://ai.facebook.com/blog/-teaching-ai-to-plan-using-language-in-a-new-open-source-strategy-game/

🔗 Teaching AI to plan using language in a new open-source strategy game
Facebook AI has open sourced MiniRTSv2, a real-time strategy game designed to test and evaluate a range of AI techniques related to reinforcement learning, hierarchical decision-making and natural language processing.

​Integrative analysis of single-cell multi-omics data using deep learning

🔗 Integrative analysis of single-cell multi-omics data using deep learning
Single-cell RNA sequencing (scRNA-seq) has offered a comprehensive and unbiased approach to profile immune cells including T cells with a…

​Creating a data set and a challenge for deepfakes

https://ai.facebook.com/blog/deepfake-detection-challenge/

🔗 Creating a data set and a challenge for deepfakes
Facebook is partnering with academic researchers and other industry leaders to create the DeepFake Detection Challenge.

​Lost in Translation. Found by Transformer.

🔗 Lost in Translation. Found by Transformer.
Tackle the mystery of Transformer model used by GPT-2, BERT

🎥 KNN Algorithm and its Evaluation using Confusion Matrix - Machine Learning in Python
👁 1 раз ⏳ 591 сек.
👉 KNN Algorithm and Evaluating the same with Confusion Matrix : Machine Learning in Python using Scikit Learn

👆 This video explains how the KNN or K Nearest Neighbour Algorithm works and how we can evaluate the performance using Confusion Matrix using Scikit Learn

👉 The KNN Algorithm: https://youtu.be/R6Jcz1UNz3g
👉 The Iris Dataset: https://youtu.be/rOZezzKEHpY
👉 Using Train Test Split: https://youtu.be/socWy13ZfKc

Feel free to check out and follow CodesBay @

👉 YouTube: https://www.youtube.com/Cod

🎥 Introduction to Neural Networks - Part 2 | Machine Learning Career Track
👁 3 раз ⏳ 7212 сек.
Introduction to Neural Networks class is part of Machine Learning Career Track at Code Heroku. Get started in our ML Career Track for Free: http://www.codeheroku.com/ml

We did face some issues towards the end of the class; but here is the completed version.
The issue was that we were missing a reshape of labels y. Check the notebook below for completed code:
Completed Jupyter Notebook:
https://neuralnetworks-hellocodeheroku.notebooks.azure.com/j/notebooks/nn1.ipy

Dataset: https://notebooks.azure.com/hel

​Facebook Research at Interspeech 2019

https://ai.facebook.com/blog/facebook-research-at-interspeech-2019/

Sequence-to-Sequence Speech Recognition with Time-Depth Separable Convolutions

https://research.fb.com/publications/sequence-to-sequence-speech-recognition-with-time-depth-separable-convolutions/

Unsupervised Singing Voice Conversion

https://research.fb.com/publications/unsupervised-singing-voice-conversion/
Наш телеграм канал - tglink.me/ai_machinelearning_big_data

🔗 Facebook research at Interspeech 2019
Facebook is at Interspeech 2019! For those attending the conference in Graz, Austria this week, be sure to stop by booth F7 to connect with recruiters, researchers, and software engineers about speech research at Facebook. Learn more about Facebook Research at Interspeech in our blog..

​Обработка неструктурированных текстов
Поиск организация и манипулирование

В книге описаны инструменты и методы обработки неструктурированных текстов. Прочитав ее, вы научитесь пользоваться полнотекстовым поиском, распознавать имена собственные, производить кластеризацию, пометку, извлечение информации и автореферирование. Знакомство с фундаментальными принципами сопровождается изучением реальных применений.

Издание предназначено для читателей без подготовки в области математической статистики и обработки естественных языков. Примеры написаны на Java, но сами идеи могут быть реализованы на любом языке программирования.

📝 taming-text.pdf - 💾10 542 328

🎥 5 Beginner Friendly Steps to Learn Machine Learning
👁 7 раз ⏳ 822 сек.
This video breaks down practical steps on how to learning machine learning with Python. It's the video I wish I had watched when I started learning machine learning.

Blog post version of this video - https://danielbourke.ghost.io/5-beginner-friendly-steps-to-learn-machine-learning/

Other Links Mentioned (in order)

Step 1 - Learn Python, data science tools and machine learning concepts
Elements of AI - https://www.elementsofai.com/
Python for Everybody on Coursera - https://bit.ly/pythoneverybodycoursera

🎥 "Explainable AI: the apex of human and machine learning" by Baxter Eaves
👁 1 раз ⏳ 2492 сек.
Black Box AI technologies like Deep Learning have seen great success in domains like ad delivery, speech recognition, and image classification; and have even defeated the world's best human players in Go, Starcraft, and DOTA. As a result, adoption of these technologies has skyrocketed. But as employment of Black Box AI increases in safety-intensive and scientific domains, we are learning hard lessons about their limitations: they go wrong unexpectedly and are difficult to diagnose.

From these failures, a n

​30 Helpful Python Snippets That You Can Learn in 30 Seconds or Less
https://towardsdatascience.com/30-helpful-python-snippets-that-you-can-learn-in-30-seconds-or-less-69bb49204172

🔗 30 Helpful Python Snippets That You Can Learn in 30 Seconds or Less
Short Python snippets that you can quickly learn and use in your work or personal needs

🎥 Python Voice Assistant Tutorial #8 - Opening Programs/Applications
👁 1 раз ⏳ 570 сек.
In this python voice assistant tutorial I will be showing how to open programs from python code. Specifically we will open the program/application notepad and save a note that the user has instructed us to write down.

Text-Based Tutorial: Coming Soon...

*****
Enroll in The Fundamentals of Programming w/ Python
https://tech-with-tim.teachable.com/p/the-fundamentals-of-programming-with-python

Instagram: https://www.instagram.com/tech_with_tim
Website https://techwithtim.net
Twitter: https://twitter.com/Te

​Automating Machine Learning Models on AWS

🔗 Automating Machine Learning Models on AWS
Using AWS Lambda, S3 and EC2

​Deep Learning: Predicting Skin Cancer

🔗 Deep Learning: Predicting Skin Cancer
Build a Convolutional Neural Network using Keras on Python to recognize benign/malignant melanoma cells.

​Geocode with Python

🔗 Geocode with Python
How to Convert physical addresses to Geographic locations → Latitude and Longitude

​Getting Started With Bounding Box Regression In TensorFlow

🔗 Getting Started With Bounding Box Regression In TensorFlow
Bounding box regression could be your first wonderful step in the world of object detection.

🎥 PASS SUMMIT 2016 - Using Azure Machine Learning to Predict Consumer Price Index
👁 1 раз ⏳ 4094 сек.
Inflation is one of the economic phenomena that receive particular attention from public policy actors, because of its effects on the allocation of resources, the distribution of income, economic development, and on the wellbeing of societies. Therefore, having an early and reliable vision of inflation enables defining appropriate anti-inflationary policies to achieve stability in the purchasing power of currencies.

Through leveraging Azure+PowerBI resources for data scraping, analytics, and visualization,