ProjectPro

FEBRUARY 28, 2022

Let us explore what models they are using to build the Facial Emotion Recognition Project. It aims to locate a hyperplane in an N-dimensional space that segregates the categories of data points to discover a plane with the maximum margin separation. we will use the TensorFlow framework to build each layer of our model from scratch.

Coding 52

Coding Project Deep Learning Datasets 52

ProjectPro

MARCH 19, 2021

OpenAIs GPT-3, the most powerful and largest artificial intelligence model trained on 45TB of data and run through 175 billion parameters can produce text so human-like that it’s equally astonishing and eerie. It’s actually not, the incredible model GPT3 is a better writer than most humans. Haha.Just Kidding!

Datasets 40

Datasets Python Machine Learning Algorithm 40

ProjectPro

AUGUST 13, 2021

You will use a dataset tagged with a category for the questions that the business is likely to receive. Neural Networks Neural networks are one of the most widely used Machine Learning models by Data Scientists. Official GitHub Repository: Google Research: TensorFlow code and pre-trained models for BERT 3.

Machine Learning 40

Machine Learning Project Deep Learning Datasets 40

Rockset

MARCH 28, 2024

[Building such a recommendation system] ( [link] ) that deals efficiently with high-dimensional data to find accurate, relevant, and similar items in a large dataset requires effective and efficient vectorization, vector indexing, vector search, and retrieval which in turn demands robust databases with optimal vector capabilities.

Systems 52

Systems Building Database Utilities 52

Netflix Tech

DECEMBER 10, 2020

In this post we explore how machine learning and statistical modeling can aid creative decision makers in tackling these questions at a global scale. Our approach is rooted in transfer learning , whereby performance on a target task is improved by leveraging model parameters learned on a separate but related source task.

Machine Learning 94

Machine Learning Entertainment Metadata Consulting 94

Tweag

OCTOBER 11, 2023

Also assume that we have some prior knowledge about how this data is produced, so it makes sense to express this knowledge as a Bayesian model , and use Bayesian machine learning to infer the best estimate of the state of the robot, phone, or object. Then our program should be able to react continuously in real time to this estimate.

Machine Learning 72

Machine Learning Algorithm Programming Process 72

Snowflake

MARCH 30, 2023

A 2016 data science report from data enrichment platform CrowdFlower found that data scientists spend around 80% of their time in data preparation (collecting, cleaning, and organizing of data) before they can even begin to build machine learning (ML) models to deliver business value. ML workflow, ubr.to/3EJHjvm

Engineering 84

Engineering Raw Data Data Science Scala 84

Rockset

AUGUST 26, 2022

Every predetermined time period, the agents would scan the applications for newly-entered or uploaded data -- everything from highly-compressed herd genetic data, to dimensional models. There, the data is converted, tagged with metadata, cleaned, and de-duplicated in preparation for queries.

IT 52

IT Food Data Lake Aggregated Data 52

U-Next

MARCH 13, 2023

In order to translate visual data, computer vision models need features and contextual data discovered during training. Models can understand photos and videos to perform prediction or decision-making tasks. The model can learn to distinguish between similar images if given a sizable enough dataset.

Deep Learning 73

Deep Learning Machine Learning Datasets Healthcare 73

dbt Developer Hub

JUNE 19, 2020

By default, dbt models are materialized as “views”. This removes the need to declare any models as views. If all of your models in a folder are tables , define the materialization on the dbt_project.yml file rather than on the model file. This removes clutter from the model file. Should the model be incremental?

Project 40

Project BI SQL Utilities 40

ProjectPro

AUGUST 9, 2021

Libraries panda s, sklearn, NumPy This project will evaluate the following four modelling approaches to build a music recommender system - Logistic regression Logistic regression is the simplest of all the algorithms. It resides in python as a linear model in the sklearn library. The classification uses the following models.

Data Science 52

Data Science Python Project Datasets 52

ProjectPro

JULY 9, 2021

Before we dive into the technical details of the deep learning models, let us first understand how deep learning proves to be beneficial over traditional machine learning. Different deep learning models use different activation functions like ReLU (Rectified Linear Unit), Sigmoid, etc. In that case, this article is for you.

Deep Learning 40

Deep Learning Algorithm Machine Learning Datasets 40

AltexSoft

JULY 18, 2023

It has in-memory computing capabilities to deliver speed, a generalized execution model to support various applications, and Java, Scala, Python, and R APIs. It extends the functionality of Spark to deal with graph-parallel computations, letting users model and transform their data as graphs.

Big Data 52

Big Data Data Process Process Hadoop 52

ProjectPro

AUGUST 17, 2021

Work On Real-World Hands-On Computer Vision Projects Read Some Books on Modern Computer Vision Learn Mathematical Concepts Read Research Papers Experiment with Machine Learning and Deep Learning Models Computer Vision Engineer Salary - How Much do they Earn? Who is a Computer Vision Engineer?

Engineering 40

Engineering Deep Learning Machine Learning Algorithm 40

ProjectPro

OCTOBER 20, 2021

Vertex AI (Google) : Google recently (May 2021) launched a unified AI platform to build, deploy and scale machine learning models for individuals and enterprises. This AutoML application also includes MLOps tools to manage data and models at Scale. Essentially, it is using pre-trained models and customizing them for your use case.

Machine Learning 52

Machine Learning Algorithm Government Data Science 52

ProjectPro

JUNE 24, 2021

Access Solution to Analysis of San Francisco’s Employees' Salaries 5) Topic Modelling using K-means clustering Topic modelling is a text-mining technique that is used to determine the context of a document in a few words or in other words, to find the topics covered in a particular document.

Data Analytics 40

Data Analytics Project Insurance Hadoop 40

ProjectPro

JULY 30, 2021

It is an operational data system for handling and providing machine learning attributes to models that have been deployed. Thus, banks need to have a decent number of borrowers to generate profits. They are widely used to effortlessly maintain the consistency of data between training and deployment.

Machine Learning 40

Machine Learning Project Deep Learning Banking 40

ProjectPro

MAY 31, 2021

A big data project is a data analysis project that uses machine learning algorithms and different data analytics techniques on a large dataset for several purposes, including predictive modeling and other advanced analytics applications. Lastly, your predictive model needs to be operationalized for the project to be truly valuable.

Big Data 52

Big Data Coding Project Hadoop 52

DoorDash Engineering

APRIL 12, 2023

Limited features The scalability challenges also impeded the implementation of advanced features, such as automated dimensional analysis for slicing and dicing the results by qualitative attributes. Data modeling Our platform requires access to data at the raw fact or event level, not just the aggregates.

SQL 82

SQL Metadata Raw Data Government 82