Build a Neural Network Machine Learning Model | Next Word Prediction in Python

In this video, we learn how to build a neural network machine learning model that predicts the next word of a given text sequence. We also use this model, to generate text.

Bixly: https://bixly.com/nn 

📁 GitHub: https://github.com/NeuralNine

🎵 Outro Music From: https://www.bensound.com/

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Build a Neural Network Machine Learning Model | Next Word Prediction in Python
Ray  Patel

Ray Patel

1625843760

Python Packages in SQL Server – Get Started with SQL Server Machine Learning Services

Introduction

When installing Machine Learning Services in SQL Server by default few Python Packages are installed. In this article, we will have a look on how to get those installed python package information.

Python Packages

When we choose Python as Machine Learning Service during installation, the following packages are installed in SQL Server,

  • revoscalepy – This Microsoft Python package is used for remote compute contexts, streaming, parallel execution of rx functions for data import and transformation, modeling, visualization, and analysis.
  • microsoftml – This is another Microsoft Python package which adds machine learning algorithms in Python.
  • Anaconda 4.2 – Anaconda is an opensource Python package

#machine learning #sql server #executing python in sql server #machine learning using python #machine learning with sql server #ml in sql server using python #python in sql server ml #python packages #python packages for machine learning services #sql server machine learning services

Ray  Patel

Ray Patel

1619643600

Top Machine Learning Projects in Python For Beginners [2021]

If you want to become a machine learning professional, you’d have to gain experience using its technologies. The best way to do so is by completing projects. That’s why in this article, we’re sharing multiple machine learning projects in Python so you can quickly start testing your skills and gain valuable experience.

However, before you begin, make sure that you’re familiar with machine learning and its algorithm. If you haven’t worked on a project before, don’t worry because we have also shared a detailed tutorial on one project:

#artificial intelligence #machine learning #machine learning in python #machine learning projects #machine learning projects in python #python

Top Machine Learning Projects in Python For Beginners [2021] | upGrad blog

If you want to become a machine learning professional, you’d have to gain experience using its technologies. The best way to do so is by completing projects. That’s why in this article, we’re sharing multiple machine learning projects in Python so you can quickly start testing your skills and gain valuable experience.

However, before you begin, make sure that you’re familiar with machine learning and its algorithm. If you haven’t worked on a project before, don’t worry because we have also shared a detailed tutorial on one project:

The Iris Dataset: For the Beginners

The Iris dataset is easily one of the most popular machine learning projects in Python. It is relatively small, but its simplicity and compact size make it perfect for beginners. If you haven’t worked on any machine learning projects in Python, you should start with it. The Iris dataset is a collection of flower sepal and petal sizes of the flower Iris. It has three classes, with 50 instances in every one of them.

We’ve provided sample code on various places, but you should only use it to understand how it works. Implementing the code without understanding it would fail the premise of doing the project. So be sure to understand the code well before implementing it.

#artificial intelligence #machine learning #machine learning in python #machine learning projects #machine learning projects in python #python

Mckenzie  Osiki

Mckenzie Osiki

1623906928

How To Use “Model Stacking” To Improve Machine Learning Predictions

What is Model Stacking?

Model Stacking is a way to improve model predictions by combining the outputs of multiple models and running them through another machine learning model called a meta-learner. It is a popular strategy used to win kaggle competitions, but despite their usefulness they’re rarely talked about in data science articles — which I hope to change.

Essentially a stacked model works by running the output of multiple models through a “meta-learner” (usually a linear regressor/classifier, but can be other models like decision trees). The meta-learner attempts to minimize the weakness and maximize the strengths of every individual model. The result is usually a very robust model that generalizes well on unseen data.

The architecture for a stacked model can be illustrated by the image below:

#tensorflow #neural-networks #model-stacking #how to use “model stacking” to improve machine learning predictions #model stacking #machine learning

sophia tondon

sophia tondon

1620898103

5 Latest Technology Trends of Machine Learning for 2021

Check out the 5 latest technologies of machine learning trends to boost business growth in 2021 by considering the best version of digital development tools. It is the right time to accelerate user experience by bringing advancement in their lifestyle.

#machinelearningapps #machinelearningdevelopers #machinelearningexpert #machinelearningexperts #expertmachinelearningservices #topmachinelearningcompanies #machinelearningdevelopmentcompany

Visit Blog- https://www.xplace.com/article/8743

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