TensorFlow Tutorial #05 Ensemble Learning
How to make an ensemble of multiple Neural Networks in TensorFlow. https://github.com/Hvass-Labs/TensorFlow-Tutorials This tutorial does NOT work with ...
Hvass Laboratories
How to Create a Deep Neural Network in MATLAB (Digit Recognition Example)
Hello viewers, In this video, It is explained that how one can create a deep neural network such as Convolutional Neural Network (CNN) in MATLAB. All the ...
Dr. Ajay Kumar Verma
Classifying Hand Written Digits Using TensorFlow | Deep Learning Tutorial: Part -3 | Edureka
Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Deep Learning With TensorFlow playlist here: ...
edureka!
Machine Learning Tutorial Python - 11 Random Forest
Random forest is a popular regression and classification algorithm. In this tutorial we will see how it works for classification problem in machine learning. It uses ...
codebasics
scikit-learn Skills: Employing Ensemble Methods with scikit-learn Course Preview
Join Pluralsight author Janani Ravi as she walks you through a preview of her "Employing Ensemble Methods with scikit-learn" course found only on ...
Pluralsight
Machine Learning: Konsep Bagging Ensemble
Konsep Bootstrap Aggregating (Bagging)
RumahKoding
Open architectures based on one-class classifiers for writer identification
La reconnaissance d'écriture manuscrite est l'un des plus vieux problèmes qui ait été posé à l'intelligence artificielle. L'identification du signataire et la ...
Meetup Machine Learning Rennes
Machine Learning Project in Python | Classification - PART 1
machinelearning #python #datascience Following our mini-tutorial series in machine learning with python, we will do a 2 PART predictive modelling machine ...
Pinoydatascientist
Training a machine learning model with scikit-learn
Now that we're familiar with the famous iris dataset, let's actually use a classification model in scikit-learn to predict the species of an iris! We'll learn how the ...
Data School
[Python Project] Recognizing Handwritten Digits with Python
This project is a beginner-friendly Python and Machine Learning application focused on building a logistic regression model to analyze and recognize ...
TheCodex
Machine learning at the speed of light | Piotr Antonik
Photonics has long been considered an attractive substrate for the next generation of computing and machine learning. Reservoir computing significantly ...
Computer Assisted Medical Interventions
Bagging Explained for Beginners - Ensemble Learning
In this video, our instructor will explain one type of ensemble learning called "Bagging". We will discuss the following in this video: (0:00:10) Introduction ...
AI Sciences
MIT Deep Learning Genomics - Lecture 1 - Machine Learning Intro (Spring 2020)
MIT 6.874 Lecture 1. Spring 2020 Lecturer: David Gifford Course website: https://mit6874.github.io/ Lecture 1 slides: ...
Manolis Kellis
Visual Guide to Gradient Boosted Trees (xgboost)
Gradient Boosted Trees are everywhere! They're very powerful ensembles of Decision Trees that rival the power of Deep Learning. Learn how they work with ...
Econoscent
Pytorch Neural Network example
An example and walkthrough of how to code a simple neural network in the Pytorch-framework. Explaining it step by step and building the basic architecture of ...
Aladdin Persson
3.1-Datasets in Scikit Learn Library - البيانات الجاهزة فى مكتبة سايكت ليرن
لنك تحميل الكتاب https://scikit-learn.org/0.18/_downloads/scikit-learn-docs.pdf لنك الكود والشرح ...
Ahmed Yousry
Machine Learning Tutorial Python - 16: Hyper parameter Tuning (GridSearchCV)
In this python machine learning tutorial for beginners we will look into, 1) how to hyper tune machine learning model paramers 2) choose best model for given ...
codebasics
Classify Data Using the Classification Learner App
Classification Learner lets you perform common supervised learning tasks such as interactively exploring your data, selecting features, specifying validation ...
MATLAB
[Code] Neural Network Ensemble Deep Dive (Episode 2)
In this episode, we take our deep dive two steps further and set up code to load the MNIST dataset into a tf.data.Dataset and then we set up and begin training ...
Garett MacGowan
SVM : (1) preparing data
Ho Yeon Park
Introduction to the Open Set Recognition Problem
This video is about Introduction to the Open Set Recognition Problem.
ComputerVisionFoundation Videos
Deciphering doctor's handwriting with deep learning by Ignaz Wanders
Even in 2019, there is still a lot of handwriting done by doctors, simply because not all use cases can be digitized easily. For the Flemish Government, this ...
Devoxx
Sergey Shilin: How to win a gold medal on Kaggle
Presented at PyData Montreal on July 18th, 2019 Abstract: Why Data Science may be a lot of fun. Tips and tricks that help you win any machine learning ...
PyData Montreal
Applying Machine Learning Like a Responsible Adult
In this 2015 GDC session, Havok's Ben Sunshine-Hill and The University of Pennsylvania's Aline Normoyle describe key concepts from machine learning, such ...
GDC
Lecture 16 | Adversarial Examples and Adversarial Training
In Lecture 16, guest lecturer Ian Goodfellow discusses adversarial examples in deep learning. We discuss why deep networks and other machine learning ...
Stanford University School of Engineering
Convolution Neural Networks | Machine Learning Career Track
Convolution Neural Networks are one of the most popular Neural Networks especially for data which has high spatial correlation such as images and videos.
Code Heroku
Machine Learning Basics Course for Beginners in 3 Hours | FULL COURSE | 2021
This course is designed to be simple and fun without all of complex math and boring explanations. Each theoretical lecture is crafted using whiteboard ...
Augmented Startups
Stanford CS229: Machine Learning | Summer 2019 | Lecture 1 - Introduction and Linear Algebra
Anand Avati Computer Science, PhD To follow along with the course schedule and syllabus, visit: http://cs229.stanford.edu/syllabus-summer2019.html To get ...
stanfordonline
Scikit-Learn Course - Machine Learning in Python Tutorial
Scikit-learn is a free software machine learning library for the Python programming language. Learn about machine learning using scikit-learn in this full course.
freeCodeCamp.org
Intro to Machine Learning with scikit-learn - Part 1 - Strata Hadoop San Jose 2016
Katrina Riehl (Continuum Analytics) and Jake Vanderplas (eScience Institute) present Part 1 of 'Intro to Machine Learning with scikit-learn' at the Strata + ...
Anaconda, Inc.
Basics of Machine Learning to Detect Diabetes with MATLAB
If you like this video, don't forget to subscribe it. Visit my technical blog for codes and technical posts https://algo.volganga.com/ For latest updates join me on ...
Akhilesh Kumar
PyTorch Tutorial 14 - Convolutional Neural Network (CNN)
In this part we will implement our first convolutional neural network (CNN) that can do image classification based on the famous CIFAR-10 dataset. We will learn: ...
Python Engineer
Managed Modularity for Deep Neural Networks - Prof. Gavin Brown, University of Manchester
Gavin Brown is Professor of Machine Learning and Director of Research for the School of Computer Science, at the University of Manchester. This talk was ...
Arm Research
Loading in your own data - Deep Learning basics with Python, TensorFlow and Keras p.2
Welcome to a tutorial where we'll be discussing how to load in our own outside datasets, which comes with all sorts of challenges! First, we need a dataset.
sentdex
RANDOM FOREST CLASSIFICATION-MATLAB (with Complete Code & Data)
Decision Tree Classifier Code: clc clear all close all warning off data=readtable('study_data.csv'); k=["High","Low"]; l=[1,0]; g=data.knowledge_level; ...
Knowledge Amplifier
Deep Learning - TP 03 - Reconnaissance de chiffres manuscrits avec Keras
Cette vidéo fait partie d'une formation au Deep Learning en deux jours, en français. Avant de visionner cette vidéo, il est recommandé de prendre connaissance ...
formation-deep-learning
Introduction to Machine Learning - Simon Trebst - May 31, 2017
In this first lecture I will give a pedagogical introduction to machine learning with a focus on conceptual aspects of the main algorithms including artificial neural ...
Cornell Laboratory of Atomic and Solid State Physics
Intro to Feature Engineering with TensorFlow - Machine Learning Recipes #9
Hey everyone! Here's an intro to techniques you can use to represent your features - including Bucketing, Crossing, Hashing, and Embedding - and utilities ...
Google Developers
Nicolas Papernot & Patrick McDaniel- Adversarial Examples in Machine Learning AIWTB 2017
Nicolas Papernot, Director of Institute for Network and Security Research, and Patrick McDaniel, Computer Security Graduate Research Assistant & Google PhD ...
With The Best
Keras Tutorial For Beginners | What is Keras | Keras Sequential Model | Keras Training | Intellipaat
#KerasTutorialForBeginners #WhatIsKeras #KerasTraining #KerasTutorial #KerasForBeginners #KerasSequentialModel #Intellipaat The following questions ...
Intellipaat
Beyond Machine Learning:Delivering Technology for People through Explainable AI
Freddy Lecue, Accenture Labs.
Connected Data London
Tutorial 6 - Transfer learning & Domain adaptation | Deep Learning on Computational Accelerators
Given by Aviv Rosenberg @ CS department of Technion - Israel Institute of Technology.
Prof. Alex Bronstein
