Machine Learning

Career Machine Learning

Binary Tree Algorithms for Technical Interviews – Full Course

Learn how to implement binary tree algorithms and how to use them to solve coding challenges. Course Contents: (0:00:00) Course Introduction (0:01:09) What is a Binary Tree? (0:11:28) Binary Tree Node Class (0:14:19) Depth First Values – (https://structy.net/problems/depth-first-values) (0:36:00) Breadth First Values – (https://structy.net/problems/breadth-first-values) (0:47:43) Tree Includes – (https://structy.net/problems/tree-includes) (1:05:35) Tree Sum – (https://structy.net/problems/tree-sum) (1:19:53) […]

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Databricks Machine Learning

Scaling AutoML-Driven Anomaly Detection with Luminaire

Zillow has built an orchestration framework around Luminaire, our open-source python library for hands-off time-series Anomaly Detection. Luminaire provides a suite of models and built-in AutoML capabilities which they process with Spark for distributed training and scoring of thousands of metrics. In this talk, learn the architecture of this framework and performance of the Luminaire […]

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Machine Learning

Machine Learning Course for Beginners

Learn the theory and practical application of machine learning concepts in this free comprehensive course for beginners. 💻 Code on GitHub Course Time Stamps: (0:00:00) Course Introduction (0:04:34) Fundamentals of Machine Learning (0:25:22) Supervised Learning and Unsupervised Learning In Depth (0:35:39) Linear Regression (1:07:06) Logistic Regression (1:24:12) Project: House Price Predictor (1:45:16) Regularization (2:01:12) Support […]

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Machine Learning TensorFlow

Keras Full Course for Beginners

Keras is a high-level, deep learning API developed by Google for implementing neural networks. Written in Python, it is used to make the implementation of neural networks easy. Keras is relatively easy to learn and work with because it provides a python frontend with a high level of abstraction while having the option of multiple […]

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Machine Learning

Designing Better ML Systems: Learnings from Netflix

Savin Goyal shares lessons learned by Netflix building their ML infrastructure, and some of the tradeoffs to consider when designing or buying a machine learning system. This presentation was recorded at QCon Plus 2020.

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Machine Learning

Get Started with Dataiku: From Data to Machine Learning in 10 Minutes

This tutorial is to quickly help users become familiar with the Dataiku platform (DSS). Links for setting up the tutorial. Step 1: https://www.dataiku.com/ Step 2: https://www.dataiku.com/product/get-started/virtualbox/ Step 3: http://127.0.0.1:10000/ Step 4: https://github.com/ageron/handson-ml Step 5: https://raw.githubusercontent.com/ageron/handson-ml/master/datasets/housing/housing.csv

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Databricks Machine Learning

Weekday Demand Sensing at Walmart

WalMart is one of the most data driven organizations on the planet. The SMART Forecasting team at Walmart Labs has built an innovative, cloud-agnostic, scalable platform to improve Walmart’s ability to predict customer demand while improving item in-stocks and reducing food waste. Over a period of two years, all of Walmart’s key departments in the […]

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Azure Containers Machine Learning

Prebuilt Docker Images for Inference in Azure Machine Learning

Seth welcomes Shivani Santosh Sambare to talk about Prebuilt Docker Images for Inference in Azure Machine Learning Jump to: 00:17 Show begins 00:29 Welcome Shivani 00:38 What are the challenges working with ML environments? 01:11 Solutions to ML challenges/environments = Prebuilt Docker Images for Inference 02:12 How do I make this work with other specialized […]

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Machine Learning

Gradient Descent Explained Simply

In this video, learn about Gradient Descent and how we can use it to update the weights and bias of our AI model. Time Stamps 00:00 – what is gradient descent? 00:37 – gradient descent vs perception 01:04 – sigmoid activation function 01:45 – bias and threshold 02:06 – weighted sum – working example 02:37 […]

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