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  • The Funded: Internet TV, AI-powered recruiting chatbot among latest rounds

    An Internet TV network, a recruiting chatbot powered by artificial intelligence and a startup that helps pinpoint crop stress for farmers are among the latest Bay Area funding deals.

    Source: Business Journals
    12276
  • IBM's Watson Data Platform focuses on AI

    The IBM Watson Data Platform already provides data scientists with the ability to crunch numbers and share large data sets across different public and private clouds. Now the company has its sights set on artificial intelligence (AI), reports Enterprise Cloud News (Banking Technology's sister publication).

    Source: Banking Tech
    15417
  • Top 15 Scala Libraries for Data Science in 2018

    For your convenience, we have prepared a comprehensive overview of the most important libraries used to perform machine learning and Data Science tasks in Scala.

    Source: Kdnugget
    15183
  • Ranking Popular Distributed Computing Packages for Data Science

    We examined 140 frameworks and distributed programing packages and came up with a list of top 20 distributed computing packages useful for Data Science, based on a combination of Github, Stack Overflow, and Google results.

    Source: Kdnugget
    18723
  • Know First Step of Spark Program

    Apache Spark is an open-source cluster-computing framework. Originally developed at the University of California, Berkeley's AMPLab, the Spark codebase was later donated to the Apache Software Foundation, which has maintained it since. Spark provides an interface for programming entire clusters with implicit data parallelism and fault-tolerance.

    Source: HOB
    15051
  • Introduction to Spark

    Apache Spark is an open-source cluster-computing framework. Originally developed at the University of California, Berkeley's AMPLab, the Spark codebase was later donated to the Apache Software Foundation, which has maintained it since. Spark provides an interface for programming entire clusters with implicit data parallelism and fault-tolerance.

    Source: HOB
    8772
  • Is it Necessary to Know Big Data Before Data Analytics?

    No,but if you have some knowledge about data mining algorithms. That will be beneficial in learning data analytics. Data Analytics is a field demanding a variety of skills. Having knowledge of Hadoop is one of them.

    Source: HOB
    18117
  • What is Apache Spark and Why it is Popular among Data Scientists?

    Apache Spark is an open-source cluster computing framework for real-time processing. It has a thriving open-source community and is the most active Apache project at the moment. Spark provides an interface for programming entire clusters with implicit data parallelism and fault-tolerance.

    Source: HOB
    16317
  • Hadoop and Spark: Which one is better?

    As we know organizations from different domains are investing in big data analytics nowadays by analyzing large data sets to uncover all the hidden patterns unknown correlations, market trends, customer preferences and other useful business information. These analytical findings are helping organizations in more effective marketing, new revenue opportunities and better customer service and they're trying to get competitive advantages over rival organizations and other business benefits. An Apache Spark and Hadoop are the two of most prominent big data frameworks and people often comparing these two technologies.

    Source: HOB
    13686
  • Whom To Hire Data Scientist or Data Engineer for Data?

    Data Scientist is the very demanding role in every big organisation and they have power to unlock the hidden values in the data's. They are very good at data handling and manages data at a very huge scale.

    Source: HOB
    15723
  • Why Machine Learning Industry Can Never Grow Without Open Source of Machine Learning Platform

    Google DeepMind made their machine learning platform, DeepMind Lab, publicly available. Despite warnings from experts like Professor Stephen Hawking, Google's decision to expose its software to other developers is part of a movement to further develop the capabilities of machine learning.

    Source: HOB
    39594
  • Is Really Data Scientists Are Looking For Good Opportunities?

    Data Scientists are leaving their jobs, And according to Financial Times it's correct that data scientists usually spend 1-2 hours a week to find good opportunities. We read so many stories about data science being the sexiest job of the 21st century and the attractive sums of money that you can make as a data scientist that it can seem like the absolute dream job.

    Source: HOB
    11835
  • Collection Of Popular Big Data Tools On The Basis Of Popularity, Usefulness And Features

    Big Data industry and data science evolve rapidly and progressed a big deal lately, with multiple Big Data projects and tools launched in 2017. This is one of the hottest IT trends of 2018, along with IoT, blockchain, Artificial and Machine Learning.

    Source: HOB
    26793
  • How DevOps Play Crucial Role For Data Science?

    DevOps involves infrastructure provisioning, configuration management, continuous integration and deployment, testing and monitoring. DevOps teams have been closely working with the development teams to manage the lifecycle of applications effectively.

    Source: HOB
    24477
  • Why There Is A Demand For Proficient Data Scientist And How The Data Science Course Looks Like?

    There's clearly a shortage of data scientists to help companies use more of their data, so pursuing a career in the field puts today's students at a distinct advantage when it comes to staying away from the unemployment lines after graduation. Data science is fast becoming one of today's most in-demand careers, and in fact, the prescient Harvard Business Review declared data science as the sexiest career of the 21st century six years ago.

    Source: HOB
    33975
  • Cloud Engineers Are In Demand And What Programming Language They Should Learn?

    Cloud engineers professionals responsible for assessing a business's infrastructure and migrating different functions to a cloud-based system are in high demand, as more companies move critical business processes and applications to public, private, and hybrid cloud infrastructures.

    Source: HOB
    109989
  • Triggered Spark Gaps Market Overview, Sales, Opportunities, Supply, Share, Growth Analysis, Trends, Forecast to 2025

    Market research reports for the global Triggered Spark Gaps market included detailed segmentation of international products, analysis of supply and demand trends, 5-year forecast of market growth, volumes of Mainframes market, analysis of the production, importation and exportation, and transparent market methodology.

    Source: MGI
    2691
  • Overvoltage Spark Gaps Market Growth Analysis, Share, Demand by Regions, Types and Analysis of Key Players - Forecasts To 2025

    Market research reports for the global Overvoltage Spark Gaps market included detailed segmentation of international products, analysis of supply and demand trends, 5-year forecast of market growth, volumes of Mainframes market, analysis of the production, importation and exportation, and transparent market methodology.

    Source: MGI
    2529
  • Triggered Vacuum Spark Gaps Market Analysis and Forecasts to 2025

    Market research reports for the global Triggered Vacuum Spark Gaps market included detailed segmentation of international products, analysis of supply and demand trends, 5-year forecast of market growth, volumes of Mainframes market, analysis of the production, importation and exportation, and transparent market methodology.

    Source: MGI
    2715
  • Top 10 Data Science Skills To Land Your Highest Paying Dream Job In 2019

    In a 2017 business research article IBM predicted that the need for Data Scientists will increase by 28% by 2020, with nearly 3 million job openings for Data Science professionals.

    Source: HOB
    111504
  • Employers Actually Want Software Developers To Know Top 10 Frameworks In 2019

    Demand for many of these frameworks outpaces the supply of software developers available who know them, according to a HackerRank report.

    Source: HOB
    14031
  • High In-Demand Programming Language Frameworks & Tools For Machine Learning Engineers

    More than 1,300 people mainly working in the tech, finance, and healthcare revealed which machine-learning technologies they use at their firms, in a new O'Reilly survey.

    Source: HOB
    29787
  • 7 Tools used by Data Scientists

    A Data Scientist is an expert in using some tools which are very helpful in analyzing big data sets.

    Source: HOB
    18210
  • Beginner's Guide to understand Hadoop and Spark in Data Science

    Hadoop and Spark both are used by businesses today to process big data.

    Source: HOB
    18903
  • My simple ways to pace career in Data Science

    The role of a Data Scientist depends most on the organization he is working on.

    Source: HOB
    7917
  • Dive Into the World of Deep Learning with These Most Trusted Books

    This article will take you to the best books that you can find of Deep Learning.

    Source: HOB
    8037
  • Beginners must follow these steps to start a career in Data Science

    Starting a career in Data Science can be intimidating but with the right decisions and right choices, a beginner can start a career in Data Science and soar to greater heights in the career.

    Source: HOB
    12711
  • The 7 Habits of Successful Data Scientists

    A Data Scientist is always a person with a win win approach.If he is not having a win win approach than he is not a Data Scientist. The article presents the 7 habits that every successful Data Scientist carries.

    Source: HOB
    46548
  • Recommended: Best Online courses to learn Apache Hadoop

    Processing a large number of big datasets is a challenge faced by companies until the advent of Apache Hadoop and Spark. Hadoop and Spark provide businesses with that data processing speed that businesses have always dreamt of with their data.

    Source: HOB
    8589
  • Facing Rejection in Data Science Interviews? Follow these Guided steps to crack one.

    Diversion is the easiest option you could do after your first or many rejections in Data Science interviews but standing positively all over again and trying to crack the next interview in the next chance is the best thing you can ever do.

    Source: HOB
    8757
  • Excel these 5 Skills Today to Become a Big Data Analyst

    A Big Data Analyst is the person in the organization who collects data from various resources, clean it for further processing, converts it into another format which is easy to analyze (also called Data Munging) and finally analyze it for finding hidden patterns and useful information from it (also called insights).

    Source: HOB
    13743
  • Learn Hadoop, Spark and find out which is Best through these videos

    The rise of Big Data has raised the necessity of the organizations to adopt technologies which are good at processing big Data at higher execution speed. Hadoop and Spark are the big contenders in that.

    Source: HOB
    6960
  • Know Why Predictive Analytics is the need for Businesses today with some top Predictive Analytics Tools

    To make any business successful and work for a longer time, a Proactive and forward-looking approach is needed and this is the only approach by which businesses plan strategies for the future. Using Predictive Analytics businesses make use of their past and present data to predict future certainties.

    Source: HOB
    6114
  • Demonstrating Deep Learning Models Apache, Spark, and TensorFlow

    Neural networks have seen spectacular progress during the last few years and they are now the state of the art in image recognition and automated translation.

    Source: HOB
    10260
  • Get the most meaningful insights out of your data with these tips.

    It doesn't matter how much data businesses collect, unless they are unable to find actionable insights out of it, all data collected is useless.

    Source: HOB
    8313
  • Top Tools of Machine Learning and Artificial Intelligence which should be noticed by every Developer

    Today, it's radically changing the way we think about technology. From fraud detection to virtual assistants like Siri, AI and machine learning (ML) is going through a period of significant acceleration.

    Source: HOB
    6732
  • Keep in Mind some points before Learning Machine Learning

    Not sure which course you are referring to in particular. The general basics required for machine learning are here.

    Source: HOB
    7062
  • What is the role of a data scientist in perspective of Artificial Intelligence and machine learning work?

    A data scientist is integral to an AI or ML process, in the sense that all of these projects are depending on big data or complex inputs. The data scientist is the essential careerist who knows how to work with data to produce results.

    Source: HOB
    10236
  • Data Processing Engine: Apache Spark. Explained in Detail

    Apache Spark is the latest data processing framework from open source. It is a large-scale data processing engine that will most likely replace Hadoop's MapReduce.

    Source: HOB
    12759
  • Data Scientist should turn on their mind towards some famous Books of Data Science

    Here are some books which will help you to boost your knowledge of data science and some of its fundamental tools.

    Source: HOB
    6816
  • Higher Salary opportunity for every Data Scientist in 2019

    This article having six factors that will positively influence the salary of a Data Scientist. So here are six factors through which you can easily optimize your Data Scientist salary.

    Source: HOB
    10173
  • Higher Level Courses of Machine Learning enables your Certifications

    Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome.

    Source: HOB
    7560
  • Some Famous Deep Learning Frameworks

    Fortunately, some brilliant minds have created and generously open-sourced several deep learning frameworks that can be easily integrated by people with little to no knowledge of machine learning technology.

    Source: HOB
    6243
  • Where can you start learning Data Science?

    Some easy resources from where beginners can start learning data science and its model for easy growth.

    Source: HOB
    6705
  • Big Data Courses with Its famous Frameworks: Apache, Hadoop, etc

    Interested in increasing your knowledge of the Big Data landscape? This course is for those new to data science and interested in understanding why the Big Data Era has come to be.

    Source: HOB
    7224
  • Famous Course : The Ultimate Hands-On Hadoop-Tame your Big Data!

    The world of Hadoop and Big Data can be intimidating - hundreds of different technologies with cryptic names form the Hadoop ecosystem.

    Source: HOB
    6249
  • Top Big Data Certifications for Professionals in 2019

    Drive better business decisions with an overview of how big data is organized, analyzed, and interpreted. Apply your insights to real-world problems and questions.

    Source: HOB
    7878
  • How Zoomcar gained popularity through Data Science?

    The rapid expansion of Zoomcar's fleet size and the high volume of data generated from its customers forced the company to invest in data-driven technologies.

    Source: HOB
    10287
  • Have good hands-on Apache Spark: Deep Learning Framework

    Apache Spark is the buzzword in the big data industry right now, especially with the increasing need for real-time streaming and data processing.

    Source: HOB
    8397
  • Some courses which will help you to master Deep Learning

    Deep Learning is one of the most highly sought after skills in tech. We will help you become good at Deep Learning.

    Source: HOB
    5796
  • For Data Science do you need to learn any Programming Language?

    Therefore, in order to gain knowledge and become a professional worker, you need to have a brief idea about at least one of these languages that are required in Data Science.

    Source: HOB
    5199
  • Go Big with these Big Data Courses

    Learn how big data is driving organizational change and essential analytical tools and techniques, including data mining and PageRank algorithms.

    Source: HOB
    5619
  • Skills Machine Learning Engineer Must have

    Machine learning is all about making computers to perform intelligent tasks without explicitly coding. This is achieved by training the computer with lots and lots of data.

    Source: HOB
    7098
  • Famous books for learning Apache Spark

    Quickly dive into Spark capabilities such as distributed datasets, in-memory caching, and the interactive shell

    Source: HOB
    6828
  • Understand the major technology trend driving Deep Learning, through these courses

    Deep learning engineers are highly sought after, and mastering deep learning will give you numerous new career opportunities.

    Source: HOB
    6417
  • Increase your knowledge in Big Data with these Courses

    Once you've identified a big data issue to analyze, how do you collect, store and organize your data using Big Data solutions?

    Source: HOB
    5112
  • Large-Scale Data Processing Frameworks - What Is Apache Spark?

    Apache Spark is the latest data processing framework from open source. It is a large-scale data processing engine that will most likely replace Hadoop's MapReduce.

    Source: HOB
    5670
  • Deeply learn from these Deep Learning Books

    Although interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far.

    Source: HOB
    5529
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