Knowledge Hut

JUNE 11, 2024

It is recommended to take part in a data science bootcamp and get a hands-on approach to building data science projects with Java. Importance of Java for Data Science: When it comes to data science, Java delivers a host of data science methods such as data processing, data analysis, data visualization statistical analysis, and NLP.

Java 52

Java Data Science Programming Language Scala 52

Knowledge Hut

SEPTEMBER 6, 2023

Data Science Bootcamp course from KnowledgeHut will help you gain knowledge on different data engineering concepts. It will cover topics like Data Warehousing,Linux, Python, SQL, Hadoop, MongoDB, Big Data Processing, Big Data Security,AWS and more.

Data Science 97

Data Science Certification Business Analyst Machine Learning 97

ProjectPro

JANUARY 24, 2023

The library supports scalable solutions by utilizing Python’s in-built iterators and generators for streamed data processing. It can be used for web mining, network analysis, and text processing. This means the dataset is never loaded in the system’s RAM.

Python 52

Python Project Programming Language Data Mining 52

Knowledge Hut

JUNE 10, 2024

Pattern Among the various Python frameworks available, Pattern is particularly well-suited for Data Science tasks. It provides a comprehensive set of tools for Data Mining, Machine learning, and Natural Language Processing. Easy data preprocessing and normalization. Support for multiple evaluation metrics.

Data Science 52

Data Science Python Deep Learning Machine Learning 52

U-Next

AUGUST 11, 2022

Artificial Intelligence is achieved through the techniques of Machine Learning and Deep Learning. Machine Learning (ML) is a part of Artificial Intelligence. It builds a model based on Sample data and is designed to make predictions and decisions without being programmed for it. is highly beneficial.

Medical 52

Medical Computer Science Machine Learning Scala 52

AltexSoft

JULY 27, 2021

This type of CF uses machine learning or data mining techniques to build a model to predict a user’s reaction to items. How recommender systems work: data processing phases. Any modern recommendation engine works using a powerful mix of machine learning technology and data that fuels everything up.

Machine Learning 76

Machine Learning Systems Algorithm Deep Learning 76

U-Next

AUGUST 25, 2022

Because they may utilize the functionalities of the Machine Learning libraries knowing how the methods are implemented, this helps programmers save a huge amount of time, making their lives simpler. The American Deep Learning and Machine Learning Markets are expected to be worth $80 million by 2025. TensorFlow.

Machine Learning 40

Machine Learning Deep Learning Python Data Mining 40

ProjectPro

JUNE 18, 2021

Get FREE Access to Machine Learning Example Codes for Data Cleaning, Data Munging, and Data Visualization Java vs Python for Data Science- Frameworks and Tools Python and Java provide a good collection of built-in libraries which can be used for data analytics, data science, and machine learning.

Java 52

Java Data Science Python Programming Language 52

Knowledge Hut

MAY 23, 2024

KNIME: KNIME is another widely used open-source and free data science tool that helps in data reporting, data analysis, and data mining. With this tool, data science professionals can quickly extract and transform data. Python: Python is, by far, the most widely used data science programming language.

Data Science 52

Data Science MongoDB Programming Language Hadoop 52

ProjectPro

JULY 21, 2021

Good knowledge of commonly used machine learning and deep learning algorithms. Method: The first step to start designing the Sentiment Analysis system would involve performing EDA over textual data. Of course, you will first have to use basic NLP methods to make your data suitable for the above algorithms.

Coding 52

Coding Project Deep Learning Algorithm 52

U-Next

SEPTEMBER 13, 2022

A multidisciplinary field called Data Science involves unprocessed data mining, its analysis, and discovering patterns utilized to extract meaningful information. The fundamental building blocks of Data Science are Statistics, Machine Learning, Computer Science, Data Analysis, Deep Learning, and Data Visualization. .

Machine Learning 40

Machine Learning Data Science Deep Learning Algorithm 40

ProjectPro

DECEMBER 21, 2021

Data Engineer Data engineers develop and maintain the data platforms that machine learning and AI systems rely on. Their primary task is to create information systems for the following purposes- data acquisition, data process development, data conversion, data mining, and data pattern discovery, etc.

Machine Learning 52

Machine Learning Engineering Algorithm Data Science 52

ProjectPro

JUNE 9, 2021

For optimum use of the data, the data engineer and data scientist must work closely together for efficient data processing. A data scientist can only play his part in the work done by the data engineer. On the other hand, a data engineer must have a solid database management base.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Science 52

Databand.ai

DECEMBER 20, 2022

Eric is certified in Lean Six Sigma and experienced in Python, SQL, and machine learning. He has also completed courses in data analysis, applied data science, data visualization, data mining, and machine learning. You can also check out his Medium page the boasts 7M+ views.

Data Analytics 52

Data Analytics Google Cloud Data Science Data Mining 52

Knowledge Hut

JANUARY 19, 2024

For beginners in the curriculum for self-study, this is about creating a scalable and accessible data hub. Importance: Efficient organization and retrieval of data. Consolidating data for a comprehensive view. Flexibility in storing and analyzing raw data. Data Mining Data mining is the treasure hunt of data science.

Data Science 52

Data Science Machine Learning Algorithm Datasets 52

AltexSoft

MAY 12, 2023

Analysis of structured data is typically performed using SQL queries and data mining techniques. Unstructured data , on the other hand, is unpredictable and has no fixed schema, making it more challenging to analyze. Without a fixed schema, the data can vary in structure and organization. Hadoop, Apache Spark).

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Knowledge Hut

FEBRUARY 7, 2023

This tool is also one of the Data Science Bootcamp prerequisites and has to be installed on a system or you can work on online development platforms like Google Colab. Gets slow when working on heavy Deep Learning Algorithms 2. Centralize data resources Data Science Platforms have a unified location for all work.

Data Science 52

Data Science Google Cloud Machine Learning 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

Knowledge Hut

APRIL 20, 2023

Data mining, machine learning, statistical analysis, programming languages (Python, R, SQL), data visualization, and big data technologies. Cybersecurity vs Data Science: Career Data science vs cybersecurity careers, well, both provide good employment options.

Data Science 52

Data Science Computer Science Healthcare Recruitment 52

ProjectPro

AUGUST 16, 2021

Machine Learning Projects on Classification 2. Machine Learning Projects on Prediction 3. Machine Learning Projects on Computer Vision 4. Machine Learning Projects on Natural Language Processing (NLP) 5. Deep Learning and Neural Network Projects 6. It's best practice to remove them beforehand.

Machine Learning 40

Machine Learning Coding Project Deep Learning 40

U-Next

AUGUST 11, 2022

The first step is capturing data, extracting it periodically, and adding it to the pipeline. The next step includes several activities: database management, data processing, data cleansing, database staging, and database architecture. Consequently, data processing is a fundamental part of any Data Science project.

Data Science 40

Data Science Data Cleanse Unstructured Data Machine Learning 40

U-Next

AUGUST 25, 2022

The popular Machine Learning models and algorithms widely employed in the Artificial Intelligence business include supervised and unsupervised learning algorithms , random forest, k-nearest neighbor, and basics of deep learning. Machine Learning Types. Semi-Supervised Learning. Quantum Computing.

Machine Learning 40

Machine Learning Algorithm Data Mining Utilities 40

Knowledge Hut

NOVEMBER 28, 2023

Data scientists do more than just model and process structured and unstructured data; they also translate the results into useful strategies for stakeholders. The duties of a data scientist go beyond just processing and analyzing data. They also have a perfect command of statistical software and programming.

Data Science 52

Data Science Telecommunication Recruitment Finance 52

ProjectPro

AUGUST 24, 2021

to accumulate data over a given period for better analysis. There are many more aspects to it and one can learn them better if they work on a sample data aggregation project. Project Idea: Explore what is real-time data processing, the architecture of a big data project, and data flow by working on a sample of big data.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

OCTOBER 29, 2021

How then is the data transformed to improve data quality and, consequently, extract its full potential? Data Preprocessing to the rescue! Table of Contents What is Data Preprocessing? This is why we will get back to the über important topic of improving data quality by preprocessing in the later section.

Data Mining 52

Data Mining Datasets Machine Learning Metadata 52

U-Next

AUGUST 3, 2022

This definition is rather wide because Data Science is, undoubtedly, a somewhat vast discipline! Data Science is the discipline of concluding the analysis of raw knowledge using machine learning and data mining methods. What is a Data Scientist? What are Data Scientist roles?

Data Science 52

Data Science Retail Computer Science Entertainment 52

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. Concepts of deep learning can be used to analyze this dataset properly.

Big Data 52

Big Data Coding Project Hadoop 52

ProjectPro

APRIL 20, 2017

There are various kinds of hadoop projects that professionals can choose to work on which can be around data collection and aggregation, data processing, data transformation or visualization. What will you learn from this Hadoop Project? What is Data Engineering? Fetching data through Apache Hadoop.

Hadoop 40

Hadoop Big Data Coding Project 40