Databand.ai

DECEMBER 13, 2022

He also has more than 10 years of experience in big data, being among the few data engineers to work on Hadoop Big Data Analytics prior to the adoption of public cloud providers like AWS, Azure, and Google Cloud Platform. Beyond his work at Google, Deepanshu also mentors others on career and interview advice at topmate.io/deepanshu.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

Knowledge Hut

JANUARY 22, 2024

Some common specializations include: Machine Learning and AI These courses provide in-depth knowledge of machine learning algorithms like regression, classification, clustering, deep learning and natural language processing. The project-based learning helps students build an impressive portfolio to showcase their skills.

Data Science 52

Data Science Certification Education Hadoop 52

ProjectPro

JULY 17, 2021

You need to be well versed with the neural network and deep learning architectures to solve speech recognition , translation, image classification problems, etc. They may also have skills and experience in deep learning, natural language processing, neural networks, etc. The demand for mid-level AI Engineers is massive.

Engineering 40

Engineering Machine Learning Data Science Algorithm 40

ProjectPro

JUNE 13, 2018

Whether you are taking your first steps into the cloud or are looking forward to increasing your marketability, this is the best time to expand your cloud skill set and become a certified AWS professional. The success of employability in today’s cloud jobs market is to acquire cross-platform skills.

AWS 52

AWS Certification Amazon Web Services Cloud Computing 52

ProjectPro

AUGUST 24, 2021

Build a Job Winning Data Engineer Portfolio with Solved End-to-End Big Data Projects 1) Smart IoT Infrastructure In this IoT project , you will be discussing a general architecture for building smart IoT infrastructure. Create a service account on GCP and download Google Cloud SDK(Software developer kit).

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

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. Data Science on Google cloud platform Google Cloud is one of the best data science learning platforms.

Data Science 52

Data Science Google Cloud Machine Learning AWS 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.

Machine Learning 40

Machine Learning Coding Project Deep Learning 40

Knowledge Hut

MARCH 19, 2024

Select EC2 accelerated computing instances if you require a lot of processing power and GPU capability for deep learning and machine learning. SPS Commerce benefits from Kubernetes' flexibility and can avoid vendor lock-in, which they require to switch cloud providers.

AWS 52

AWS Amazon Web Services Hospitality Cloud Computing 52

ProjectPro

SEPTEMBER 6, 2021

So, are you ready to explore the differences between two cloud giants, AWS vs. google cloud? Amazon brought innovation in technology and enjoyed a massive head start compared to Google Cloud, Microsoft Azure , and other cloud computing services. GCP Storage Google Cloud storage provides high availability.

AWS 52

AWS Amazon Web Services Google Cloud Cloud Storage 52

ProjectPro

JANUARY 31, 2022

Provides Powerful Computing Resources for Data Processing Before inputting data into advanced machine learning models and deep learning tools, data scientists require sufficient computing resources to analyze and prepare it. Amazon Web Services , Google Cloud Platform, and Microsoft Azure support Snowflake.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

ProjectPro

MAY 31, 2021

Ace your big data interview by adding some unique and exciting Big Data projects to your portfolio. Before actually working on any big data projects, data engineers must acquire proficient knowledge in the relevant areas, such as deep learning, machine learning, data visualization, data analytics, etc.

Big Data 52

Big Data Coding Project Hadoop 52

AltexSoft

DECEMBER 15, 2021

The software will make this choice itself, picking from the existing portfolio of options the one fitting your task best. The accuracy of the forecast depends not only on features but also on hyperparameters or internal settings that dictate how exactly your algorithm will learn on a specific dataset. Source: Google Cloud Blog.

Machine Learning 59

Machine Learning Deep Learning Algorithm Telecommunication 59