Mlearning.ai

APRIL 25, 2023

Further Analysis From the first plot, we can see the frequency of content added by Netflix from 2008 to 2021. From the second plot, we can see the top 20 genres that have been added by Netflix from 2008 to 2021. plt.figure(figsize=(12,6)) df[df["type"]=="TV Show"]["release_year"].value_counts()[:20].plot(kind="bar",color="Blue")

Data Analysis 52

Data Analysis Data Analysis Python Exploratory Data Analysis 52

DataRobot Blog

APRIL 29, 2022

Prior to the financial crisis of 2008, Model Risk Management within the financial services industry was driven by industry best practices rather than regulatory standards(which brings to mind the saying “a fox guarding the hen house”). The Framework for ML Governance. More on this topic. Download now.

Machine Learning 111

Machine Learning Machine Learning Artificial Intelligence Artificial Intelligence 111

O'Reilly Media

NOVEMBER 29, 2022

The financial collapse of 2008 led to tighter regulation of banks and financial institutions. An outcomes-based strategy would look at the impact of an AI or ML solution on specific categories and subgroups of stakeholders. Even when catastrophes don’t kill large numbers of people, they often change how we think and behave.

Artificial Intelligence 111

Artificial Intelligence Artificial Intelligence AI AI 111

AWS Machine Learning Blog

JANUARY 13, 2023

Machine learning (ML) presents an opportunity to address some of these concerns and is being adopted to advance data analytics and derive meaningful insights from diverse HCLS data for use cases like care delivery, clinical decision support, precision medicine, triage and diagnosis, and chronic care management.

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AWS Analytics Analytics Machine Learning 73

O'Reilly Media

SEPTEMBER 19, 2023

” Consider the structural evolutions of that theme: Stage 1: Hadoop and Big Data By 2008, many companies found themselves at the intersection of “a steep increase in online activity” and “a sharp decline in costs for storage and computing.” And it (wisely) stuck to implementations of industry-standard algorithms.

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AWS Machine Learning Blog

FEBRUARY 10, 2023

Through a collaboration between the Next Gen Stats team and the Amazon ML Solutions Lab , we have developed the machine learning (ML)-powered stat of coverage classification that accurately identifies the defense coverage scheme based on the player tracking data. In this post, we deep dive into the technical details of this ML model.

ML 66

ML ML Machine Learning Machine Learning 66

AWS Machine Learning Blog

APRIL 18, 2023

JumpStart helps you quickly and easily get started with machine learning (ML) and provides a set of solutions for the most common use cases that can be trained and deployed readily with just a few steps. Defining hyperparameters involves setting the values for various parameters used during the training process of an ML model.

ML 66

ML ML Deep Learning Deep Learning 66

O'Reilly Media

JULY 25, 2023

And if I switch tabs to view a paper from 2008, then a song from 2008 could start up. To provide some coherence to the music, I decided to use Taylor Swift songs since her discography covers the time span of most papers that I typically read: Her main albums were released in 2006, 2008, 2010, 2012, 2014, 2017, 2019, 2020, and 2022.

AI 98

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AWS Machine Learning Blog

APRIL 18, 2023

JumpStart helps you quickly and easily get started with machine learning (ML) and provides a set of solutions for the most common use cases that can be trained and deployed readily with just a few steps. Defining hyperparameters involves setting the values for various parameters used during the training process of an ML model.

ML 52

ML ML Deep Learning Deep Learning 52

AWS Machine Learning Blog

APRIL 3, 2023

JumpStart is the machine learning (ML) hub of Amazon SageMaker that offers a one-click access to over 350 built-in algorithms; pre-trained models from TensorFlow, PyTorch, Hugging Face, and MXNet; and pre-built solution templates. This page lists available end-to-end ML solutions, pre-trained models, and example notebooks.

Natural Language Processing 77

Natural Language Processing Machine Learning Machine Learning Algorithm 77

Mlearning.ai

FEBRUARY 16, 2023

To control the risk in a worst-case scenario, such as financial crisis of 2007–2008, FinRL employs the VIX index and turbulence index. Adding risk-control index Risk-aversion reflects whether an investor prefers to protect the capital. It also influences one’s trading strategy when facing different market volatility level.

AI 52

AI AI ML ML 52

Mlearning.ai

JUNE 6, 2023

We have the IPL data from 2008 to 2017. It can also be thought of as the ‘Hello World of ML world. IPL Score Prediction with Flask app In this project, I built an IPL Score Prediction model using Ridge Regression which is just an upgraded form of Linear Regression. We will also be building a beautiful-looking interactive Flask model.

Machine Learning 52

Machine Learning Machine Learning Python Deep Learning 52

Mlearning.ai

MAY 23, 2023

We have the IPL data from 2008 to 2017. IPL Score Prediction with Flask app In this project, I built an IPL Score Prediction model using Ridge Regression which is just an upgraded form of Linear Regression. We will also be building a beautiful-looking interactive Flask model. Working Video of our App [link] 12.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Python 52

Mlearning.ai

MAY 21, 2023

We have the IPL data from 2008 to 2017. IPL Score Prediction with Flask app In this project, I built an IPL Score Prediction model using Ridge Regression which is just an upgraded form of Linear Regression. We will also be building a beautiful-looking interactive Flask model. Working Video of our App [link] 12.

Machine Learning 52

Machine Learning Machine Learning K-nearest Neighbors Python 52

Alation

AUGUST 5, 2021

Artificial Intelligence (AI) and Machine Learning (ML) As more companies implement Artificial Intelligence and Machine Learning applications to their business intelligence strategies, data users may find it increasingly difficult to keep up with new surges of Big Data.

Data Quality 52

Data Quality Data Governance Artificial Intelligence Artificial Intelligence 52

ML Review

MARCH 5, 2019

AI Distillery (Part 2): Distilling by Embedding was originally published in ML Review on Medium, where people are continuing the conversation by highlighting and responding to this story. Information Processing & Management, 24(5), 513–523. Maaten, L. D., & Hinton, G. Visualizing data using t-SNE.

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Mlearning.ai

MAY 15, 2023

This was developed in 2008 by Wes McKinney and was developed for data analysis. Pandas is an open-source, python-based library used in data manipulation applications requiring high performance. The name is derived from “Panel Data” having multidimensional data.

Python 52

Python ML ML Data Analysis 52

Tableau

DECEMBER 1, 2021

Four reference lines on the x-axis indicate key events in Tableau’s almost two-decade history: The first Tableau Conference in 2008. The first Tableau customer conference was in 2008. August 2008) because Tableau needed to gather sufficient map data to support customers around the world. Release v1.0 IPO in 2013. March 2021).

Tableau 144

Tableau ML ML Database 144

Tableau

DECEMBER 1, 2021

Four reference lines on the x-axis indicate key events in Tableau’s almost two-decade history: The first Tableau Conference in 2008. The first Tableau customer conference was in 2008. August 2008) because Tableau needed to gather sufficient map data to support customers around the world. Release v1.0 IPO in 2013. March 2021).

Tableau 98

Tableau ML ML Database 98