Knowledge Hut

MAY 2, 2024

Apache Spark was developed by a team at UC Berkeley in 2009. Since then, Apache Spark has seen a very high adoption rate from top-notch technology companies like Google, Facebook, Apple, Netflix etc. MLlib interoperates with Python’s math/numerical analysis library NumPy and also with R’s libraries.

Scala 52

Scala Hospitality Healthcare Retail 52

ProjectPro

JANUARY 19, 2022

Good knowledge of various machine learning and deep learning algorithms will be a bonus. Knowledge of popular big data tools like Apache Spark, Apache Hadoop, etc. Good communication skills as a data engineer directly works with the different teams. and their implementation on the cloud is a must for data engineers.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Knowledge Hut

FEBRUARY 11, 2023

Using technologies like Google Analytics and Online Surveys or undertaking a Digital Marketing Bootcamp , a digital marketer gains insights into marketing trends and consumer behavior. Brew Interactive The agency has been active since 2009, offering a wide range of services. Additionally, they stay current on SEO strategies.

Media 52

Media Food Recruitment Hospitality 52

Knowledge Hut

MAY 2, 2024

Here come the frameworks like Apache Spark and MapReduce to our rescue and help us to get deep insights into this huge amount of structured, unstructured, and semi-structured data and make more sense of it. Both technologies have their own pros and cons as we will see below. The data is referred from the RDD Programming guide.

Scala 96

Scala Hadoop Datasets Java 96

Knowledge Hut

NOVEMBER 28, 2023

We will discuss the different types of datasets in data science which cover disciplines like data visualization, data processing, machine learning, data cleaning, exploratory data analysis, natural language processing, and computer vision. Link to Dataset 2. Statistician Nate Silver founded FiveThirtyEight.

Datasets 96

Datasets Data Science Project Banking 96

AltexSoft

JULY 27, 2021

By utilizing ML algorithms and data, it is possible to create smart models that can precisely predict customer intent and as such provide quality one-to-one recommendations. At the same time, the continuous growth of available data has led to information overload — when there are too many choices, complicating decision-making.

Machine Learning 76

Machine Learning Systems Algorithm Deep Learning 76

ProjectPro

DECEMBER 14, 2021

Customer Churn Analysis 2. Product Sales Data Analysis 3. Marketing Campaign Insights Analysis 4. Financial Performance Analysis 5. Healthcare Sales Analysis Intermediate-Level Power BI Project Ideas 6. Loan Application Analysis 10. Airport Authority Data Analysis 12.

BI 52

BI Project Datasets Business Intelligence 52