ProjectPro

JULY 23, 2021

Machine Learning and Deep Learning have experienced unusual tours from bust to boom from the last decade. But when it comes to large data sets, determining insights from them through deep learning algorithms and mining them becomes tricky. There are a lot of deep learning frameworks available.

Deep Learning 40

Deep Learning Machine Learning Algorithm Datasets 40

U-Next

SEPTEMBER 29, 2022

A number of hyperparameters are typically included in newer algorithms. Scikit Learn . There are many Machine Learning libraries, but Scikit-learn is one of the most famous. The algorithm includes a number of calculations necessary for AI and data mining assignments, such as bunching, relapse, and order.

Management 52

Management Machine Learning Deep Learning Algorithm 52

Pinterest Engineering

MARCH 5, 2024

To make the ads Click-through rate (CTR) predictions more personalized, our team has adopted users’ real time behavior histories and applied deep learning algorithms to recommend appropriate ads to users. Model Stability: Resilient Batch Norm Improving the stability and training speed of deep learning models is a crucial task.

Machine Learning 61

Machine Learning Deep Learning Architecture Data Mining 61

ProjectPro

DECEMBER 17, 2021

Additionally, solving a collection of take-home data science challenges is a good way of learning data science as it is relatively more engaging than other learning methods. So, continue reading this blog as we have prepared an exciting list of data science take-home challenges for you.

Data Science 52

Data Science Medical Datasets Machine Learning 52

ProjectPro

JUNE 18, 2021

Instagram switched to Python as its primary programming language in 2017 and is using it ever since. Java is also used by many big companies including Uber and Airbnb to process their backend algorithms. SciKit-learn: The SciKit-learn library of Python can be used for data mining and data analysis.

Java 52

Java Data Science Python Programming Language 52

ProjectPro

JUNE 26, 2021

Here is a list of them: Use Deep learning models on the company's data to derive solutions that promote business growth. Leverage machine learning libraries in Python like Pandas, Numpy, Keras, PyTorch, TensorFlow to apply Deep learning and Natural Language Processing on huge amounts of data.

Project 40

Project Deep Learning Datasets Medical 40

ProjectPro

DECEMBER 22, 2016

Data Analyst Interview Questions and Answers 1) What is the difference between Data Mining and Data Analysis? Data Mining vs Data Analysis Data Mining Data Analysis Data mining usually does not require any hypothesis. Data analysis involves data cleaning.

Data Mining 52

Data Mining Data Cleanse Datasets Data Analysis 52