AltexSoft

AUGUST 18, 2021

Initially created with R programming language, they were translated to C# to comply with the core platform. As with any other deep learning model, it requires tons of data and a great deal of tuning to work well. As for our case, with the novelty approach, we achieved an average accuracy of of 75 percent.

Algorithm 59

Algorithm Datasets R (Programming) Machine Learning 59

ProjectPro

AUGUST 16, 2021

You can scale different variables to draw better conclusions from the data and also learn how to treat outliers in a dataset. Complete Solution: Credit Card Fraud Detection Data Science Project Data Mining Project on Wine Quality Dataset Dataset: For this project, you can use the R programming language.

Data Mining 40

Data Mining Coding Project Datasets 40

Knowledge Hut

JANUARY 16, 2024

For achieving this, the following concepts are essential for a machine learning engineer: Fourier transforms Music theory TensorFlow 8. Programming Skills Required to Become an ML Engineer Machine learning, ultimately, is coding and feeding the code to the machines and getting them to do the tasks we intend them to do.

Machine Learning 87

Machine Learning Engineering Programming Language Algorithm 87

ProjectPro

FEBRUARY 24, 2016

A data scientist must have in-depth knowledge of technologies used to tame big data and should always be willing to learn the merging ones. It is known that machine learning ( deep learning , NLP , clustering techniques), python programming , and statistics are the must-have skills for data scientists in 2023.

Hadoop 40

Hadoop Data Science Computer Science R (Programming) 40

ProjectPro

JANUARY 20, 2022

These statistics show that it's a perfect time to pursue a career in machine learning and artificial intelligence. Prerequisites to Learn Machine Learning Machine learning engineers often need a bachelor's degree in computer science, mathematics, statistics, or a related discipline.

Machine Learning 52

Machine Learning Deep Learning Algorithm Programming Language 52

Knowledge Hut

FEBRUARY 7, 2023

Pros Easily manageable for deploying any project Good community support Manage libraries, dependencies, and environments with Conda Build and train ML and deep learning models with inbuilt libraries Cons It can be a bit bulky sometimes, slowing down and lagging while you are working on your code, especially when you are on a low-end system.

Data Science 52

Data Science Google Cloud Programming Language AWS 52

ProjectPro

DECEMBER 22, 2016

How to save and reload a deep learning model in Pytorch? How to use auto encoder for unsupervised learning models? Using the Deep Learning Library ‘Datawig’ : Datawig is a library that can learn ML models using Deep Neural Networks to impute missing values into the dataset.

Data Mining 52

Data Mining Data Cleanse Datasets Data Analysis 52

ProjectPro

AUGUST 21, 2015

8) Apart from partitioning and bucketing, what are the other methods you can use for improving performance? 9) Which file format is better Parquet or ORC?

Hadoop 40

Hadoop Big Data Metadata Java 40