A good introduction to #MachineLearning and its 4 approaches:

https://towardsdatascience.com/machine-learning-an-introduction-23b84d51e6d0?gi=10a5fcd4decd

#BigData #DataScience #AI #Algorithms #ReinforcementLearning

❇️ @AI_Python_EN

Machine Learning Models

☞ https://morioh.com/p/1dc7518426c2

#TensorFlow #machinelearning

❇️ @AI_Python_EN

Named Entity Recognition Benchmark: spaCy, Flair, m-BERT and camemBERT on anonymizing French commercial legal cases

http://bit.ly/2rq1I5H
#DataScience #MachineLearning #ArtificialIntelligence #NLP

❇️ @AI_Python_EN

Deep Speech, a good #Persian podcsts about #AI

We will talk about #ArtificialIntelligence, #MachineLearning and #DeepLearning news.

https://castbox.fm/channel/Deep-Speech-id2420707?country=us

❇️ @AI_Python_EN

Best of arXiv.org for #AI, #MachineLearning, and #DeepLearning – November 2019

https://bit.ly/36OWsaD

❇️ @AI_Python_EN

XGBoost: An Intuitive Explanation
Ashutosh Nayak :
https://towardsdatascience.com/xgboost-an-intuitive-explanation-88eb32a48eff
#MachineLearning #DataScience

Decision trees are extremely fast when it comes to classify unknown records. Watch this video to know how Decision Tree algorithm works, in an easy way - http://bit.ly/2Ggsb9l

#DataScience #MachineLearning #AI #ML #ReinforcementLearning #Analytics #CloudComputing #Python #DeepLearning #BigData #Hadoop

🔥 As you know ML has proven its importance in many fields, like computer vision, NLP, reinforcement learning, adversarial learning, etc .. Unfortunately, there is a little work to make machine learning accessible for Arabic-speaking people. Arabic language has many complicated features compared to other languages. First, Arabic language is written right to left. Second, it contains many letters that cannot be pronounced by most foreigners like ض ، غ ، ح ، خ، ظ. Moreover, Arabic language contains special characters called Diacritics which are special characters that help readers pronounced words correctly. For instance the statement السَّلامُ عَلَيْكُمْ وَرَحْمَةُ اللَّهِ وَبَرَكَاتُهُ containts special characters after most of the letters. The diactrics follow special rules to be given to a certain character. These rules are construct a complete area called النَّحْوُ الْعَرَبِيُّ. Compared to English, the Arabic language words letters are mostly connected اللغة as making them disconnected is difficult to read ا ل ل غ ة. ArbML helps fixing this by implementing many open-source projects that support Arabic, ML and NLP.

https://github.com/zaidalyafeai/ARBML

#machinelearning #deeplearning #artificialintelligence #nlp

❇️ @AI_Python_EN

[MobiNetV1] Removing people from complex backgrounds in real time using TensorFlow.js in the web browser!

This code attempts to learn over time the makeup of the background of a video such that the algorithm can attempt to remove any humans from the scene. This is all happening in real time, in the browser, using TensorFlow.js.


https://lnkd.in/gsePqBH

#deeplearning #machinelearning #artificialintelligence

❇️ @AI_Python_EN

Abnormal respiratory patterns classifier may contribute to large-scale screening of people infected with COVID-19 in an accurate and unobtrusive manner.

abs: https://arxiv.org/abs/2002.05534v1

#rnn #machinelearning #ArtificialIntelligence #DeepLearning #

❇️ @AI_Python_EN

10 Useful ML Practices For Python Developers

Pratik Bhavsar:
https://medium.com/modern-nlp/10-great-ml-practices-for-python-developers-b089eefc18fc


#Python #MachineLearning #ArtificialIntelligence #DataScience #Programming

❇️ @AI_Python_EN

Breast cancer classification with Keras and Deep Learning

To analyze the cellular structures in the breast histology images we were instead leveraging basic computer vision and image processing algorithms, but combining them in a novel way.

Researcher: Adrian Rosebrock
Paper & codes : http://ow.ly/yngq30qjLye

#artificialintelligence #ai #machinelearning #deeplearning #bigdata #datascience

❇️ @AI_Python_EN

Very good news. Dataproc now lets you use NVIDIA GPUs to accelerate XGBoost in a Spark pipeline. This combination can speed up machine learning development and training up to 44x and reduce costs 14x when using XGBoost. With this kind of GPU acceleration for XGBoost, you can get better performance, speed, accuracy, and reduced TCO, plus an improved experience when deploying and training models. Spinning up elastic Spark and XGBoost clusters in Dataproc takes about 90 seconds.
https://gweb-cloudblog-publish.appspot.com/products/data-analytics/ml-with-xgboost-gets-faster-with-dataproc-on-gpus/amp/

#spark #machinelearning #xgboost #nvidia #gpu

❇️ @AI_Python_EN

ANNOUNCING PYCARET 1.0.0 - An amazingly simple, fast and efficient way to do machine learning in Python. NEW OPEN SOURCE ML LIBRARY If you are a DATA SCIENTIST or want to become one, then this is for YOU....

PyCaret is a NEW open source machine learning library to train and deploy ML models in low-code environment.

It allows you to go from preparing data to deploying a model within SECONDS.

PyCaret is designed to reduce time and efforts spent in coding ML experiments. It automates the following:

- Preprocessing (Data Preparation, Feature Engineering and Feature Selection)
- Model Selection (over 60 ready-to-use algorithms)
- Model Evaluation (50+ analysis plots)
- Model Deployment
- ML Integration and Monitoring (Power BI, Tableau, Alteryx, KNIME and more)
- ..... and much more!

Watch this 1 minute video to see how PyCaret can help you in your next machine learning project.

The easiest way to install pycaret is using pip. Just type "pip install pycaret" into your notebook.

To learn more about PyCaret, please visit the official website https://www.pycaret.org

#datascience #datascientist #machinelearning #ml #ai #artificialintelligence #analytics #pycaret

❇️ @AI_Python_EN