In this article, we will compare the most commonly used platforms and analyze their main features to help you choose one or several platforms that will provide indispensable aid for your work communication.
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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.
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Personally, I haven't learnt as much from videos & online tutorials as much I've learnt from books. Until this very moment, my tiny wooden shelf has enough books to keep me busy this winter.
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I started working at www.comet.ml a few months ago, where we are building a really amazing tool for machine learning engineers. The short of it is that we help track experiments using a single line of code that automagically saves everything to make your model reproducible. You can get great experiment logging and history without being tied to a single platform.
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This is a story about the danger of interpreting your machine learning model incorrectly, and the value of interpreting it correctly. If you have found the robust accuracy of ensemble tree models such as gradient boosting machines or random forests attractive, but also need to interpret them, then I hope you find this informative and helpful.
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Now big data and analytics lies in the heart of every organization but data will act as a garbage for data scientist until and unless they are not able to visualize the data and its impact on key activities and the business outcome.
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A portfolio of real-world projects is the best way to break into data science. This article highlights the 5 types of projects that will help land you a job and improve your career.
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Stagraph is a new simple visual interface for R, which focuses on data import, data wrangling and data visualization.
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A collection of the most exemplary examples of data visualizations, including Napoleons invasion of Russia and the iconic London Underground map.
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I came across a challenge on Kaggle called PASSNYC: Data Science for Good. Nelson Mandela was right. Education is a powerful weapon as well as one of life's greatest gifts.
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A portfolio of real-world projects is the best way to break into data science. This article highlights the 5 types of projects that will help land you a job and improve your career.
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Python continues to take leading positions in solving data science, Machine Learning, Deep Learning, Data Scraping tasks and challenges. Last year we made a blog post overviewing the Python's libraries that proved to be the most helpful at that moment.
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Appearing smart should be the top priority of every Data Scientist. This is what drives your career, right? Sarah Cooper's advice on how to appear smart in meetings is a fantastic start, but to succeed among Data Scientists is a whole other ballpark.
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In general explanation, data science is nothing more than using advanced statistical and machine learning techniques to solve various problems using data and Data Analysis. Yet, it's easier to just dive into applying some fancy machine learning algorithms -and Voila! You got the predictionâ??-â??without first understanding the data.
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In Part-2 collection of 10 Big Data Analysis Tools As Data Visualization and Sentiment Analysis Tools are mentioned. There are numerous of Big Data tools for data analysis today. Data analysis is the process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision making.
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Are you looking for Free online Data Science courses? Yes, it is possible. Data science plays a very crucial role when it comes to companies growth. Why? because with the help of Data Scientist, a company can know more about the behavior of its users or potential clients (For example - Amazon and Flipkart).
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If you're thinking of learning Python-or if you recently started learning about Python-you may be asking yourself- What exactly can I use Python for?
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This list contains free learning resources for data science, machine learning and big data related concepts, techniques, and applications. Inspired by Free Programming Books.
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A Small Real-World Project for Learning Three Invaluable Data Science Skills. As with most interesting projects, this one started with a simple question asked half-seriously: how much tuition do I pay for five
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Data visualization is helping companies worldwide to identify patterns, predict outcomes, and improve business returns. Visualization is an important aspect of data analysis. Simply put, data visualization conveys outcomes of tabular or spatial data in a visual format. Images have the power to capture attention and convey ideas clearly. This aids decision making and drives action for improvements.
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The secret is out: Data Science. Machine learning, and other data visualization skills are invaluable tools if you want to work in development. But you didn't need us to tell you that - many of you are already programming away on Python or R, and diving into projects on Kaggle or DataKind.
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:Business Intelligence is providing the right data at the right time to right people so that they can take the right decisions." The term Business Intelligence (BI) revolves around the technology-driven process for analyzing data and delivering actionable information to take brilliant business decisions. Business intelligence tool encapsulates strategies and technologies used by enterprises for data analysis of business information.
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Data is absolutely priceless and the new gold for all businesses. But it is not a cake walk to analyze it as greater things come at a greater cost. With the tremendous growth in data, we need a process to extract useful insights from the raw data.
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Marketing has evolved with new technologies which are a mixture of new science and art. Art helps you to extract the content which is creative and science is where you get to know the facts and figures, what worked and what need to be upgraded. Modern marketing does not follow the old approach, now there are multiple data points to back up data which includes many performances of the applications, data of the customer, figures of the sales, and website analytics. Data visualization showcases data which is of visual format.
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Businesses around the globe have incorporated big data in their operations to make sense of the seeming myriad data generated on a consistent basis. The adoption of big data technology and services has grown at a robust pace among end-use industries. As big data becomes more mainstream, and integration with cloud and artificial intelligence becomes more streamlined, further growth is projected.
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Is data literacy necessary in youngsters, the solution is affirmative as a result of data is currently a component of daily life. It's nearly become a responsibility of the typical subject to possess some level of data literacy and understanding. Apparently, this analysis paper argues that young learners have the power to figure with complex data sets if they're supported within the right method and if the tasks are grounded in real-life context.
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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.
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Data will continue to drive business transformations in 2019. Here are three trends that could change the business landscape over the coming year and tips to help you prepare for them. As we prepare for 2019, it's a good time to look back and reflect on the effect that data has had on global business during this past year and what might be in store in the year ahead.
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f you are willing to get into tech, and not knowing which skills you need for your career! By gaining the tech skills you can increase your marketability for the future as well. It is a very broad field as you have multiple directions where you can lead in and there are several skills which are demanding and gives you an appealing journey. Here are some skills which are demanding in 2019
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When it comes to landing a high-paying job, the thing that counts the most is the programming language practical skills you possess.
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According to estimates, 80% of world data is unstructured. This data resides in social media feeds, digital photos, emails, and audio files, to call some. Unstructured data are often onerous to research, which suggests businesses will fail to utilize the treasure hoarded wealth of data they need access to. That is wherever fashionable business intelligence tools are available in.
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Skills of data analytics have become the leading factor in terms of the advanced development and for the career perspective, the demand of the data analyst is increasing day by day. There are several online courses which you would prefer if you want to build your career as a data analyst as it will help you to learn the fundamentals of data science, the key tools of data science and the study of programming languages in the analysis of big data.
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This programming language R is developed in 1993 and was R was conceived by professors Auckland University Ross Ihaka and Robert Gentleman. R language has methods of statistics and graphics. And these methods also comprises of the machine learning algorithm, time series, linear regression, interferences of statistical and many more.
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Some Ebooks which will give enhance your knowledge for free in deep learning, Hadoop and DataViz. Here you have some links to get these free EBooks.
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How to make great-looking, fully-interactive plots with a single line of Python. The sunk-cost fallacy is one of many harmful cognitive biases to which humans fall prey.
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Big Data is immense at the moment. From a startup to a healthcare firm, from a big MNC to an agricultural field, Big Data is being used almost everywhere. Therefore, the cope in the world of Big Data is immense. Also, as the Big Data industry is pretty huge, therefore, it may not be easy to grasp complete knowledge of the department together. It can be a little scary to learn every aspect of Big Data as well as the related technologies.
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There is huge material for the people who are interested in the machine learning with python. As we moved to the new year 2019, it is a good time to again visit the concept and get the way for the new learning path for mastering machine learning with Python.
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If you're a beginner or experienced as a Data Scientist then you must aware of these data science books. Books are the best source to get insights and increase our knowledge.
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When I started working at my latest company all the reporting was done with a combination of Google Sheets and Tableau, with Tableau being the principle reporting mechanism.
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Working as a Data Scientist you will analyze data sets which are more complex and large in number as compared to a Data Analyst job.
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According to Spectrum Survey conducted by IEEE, R ranks 7th among the top 10 Programming Languages of 2018.
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We are here to provide you a list of 5 books which will play a key factor in honing your skills in Data Science and Machine Learning and sets you apart from your competitors.
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So here you can see some real-life instructors just to make sure that there is a proper effective environment of learning for students there.
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LinkedIn is a very good place for the professionals to gather, connect with others, share ideas and network. If you are in a Data Science or predictive analytics space, or if you are seeking for additional insights and what all industries are talking about, for all these LinkedIn professional groups are a great place to start.
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Data Scientists require to possess a number of skills but the most in-demand skill of a Data Scientist is one that is required by every Data Scientist to possess and which is also the most sought after skill by any recruiter hiring for a Data Scientist.
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As a learner in Data Science I also faced huge difficulty in deciding out the best online resource for me. It was frustrating at the starting and there were times when amid confusions I gave up.
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I have also been an enthusiast in the field and had explored many of the resources for the same during the starting of my career. Here, I have organized and presented these skills in a way so to provide you the best in brief.
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Sometimes its good to analyze oneself. Sometimes its good to know the reality that whether you are a good fit for your job or not. Make sure your communication is all not holding you back from being a Good Data Scientist.
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Earlier data analytics field was not more in demand but now there is a continuous growth in this field with multiple job opportunities.
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Data Science books which will benefit beginners, professionals and business people also. You can easily avail these books on Amazon at a Discounted price.
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Here you will find multiple websites offering you various courses in data science which have perks of learning and provide online lectures too as per your convenience.
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This bundle helps you dive in, with over 400 video tutorials on machine learning and data science. The lessons show you how to build machine learning algorithms and neural networks, using popular frameworks such as TensorFlow and Keras.
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With regard to a Data Scientist apart from the soft skills and the business acumen technical skills also becomes a very important part.
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Business intelligence includes the strategies or the technologies that any business uses to find relevant insights out of the business data. With the help of Business intelligence businesses takes those important decisions that are required by it to grow.
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So here are some Big Data Analytics tools which we will explore in detail in this article.
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Here are some of the data science courses which are provided online globally with online certificates and lectures are provided according to your feasibility.
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These videos will provide you with a comprehensive and detailed knowledge of Natural Language Processing, popularly known as NLP.
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Every professional data scientist should grab these courses to know much more about data science.
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The reason why many of the data scientists position remains vacant today in spite of a number of candidates applying for the position is the "lack of skills". According to a study conducted by Great Learning, 97,000 analytics and data science positions remain vacant in India due to the dearth of the skills.
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There are a number of online resources that have emerged today to teach learners the various concepts and things related to Data Science that it is a bit confusing to get started with any.
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Some books which will help data scientist to build their career with these famous Data Science courses.
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Demand for skilled data scientists continues to be sky-high, with IBM recently predicting that there will be a 28% increase in the number of employed data scientists in the next two years.
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Data Science has been ranked as one of the hottest professions and the demand for data practitioners is booming.
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Data is growing faster than ever. With the proliferation of the internet, we now generate even more information.
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In some ways, programming is like riding a bike. You're not going to forget how to write code if you don't do it for a while. On the other hand, it's a skill that takes plenty of practice to learn and even more to maintain.
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To ensure effective implementation, one of the first things to prioritize is choosing the right data analytics software. A good place to start is getting to know the leading products in the niche by checking out the best data analytics software.
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Here are some of the best courses, books, and tutorials of Programming language which will help you to master programming languages with a certified place and help you to get in-depth knowledge.
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So here in this video, we are going to talk about the top 5 business intelligence tools that stand out from the crowd and are the choice of millions of organizations who are looking for great business insights.
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Some Tutorials which will give you a brief introduction of data visualization techniques and help you master this field.
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Practical Data Visualization techniques, tips, and tricks for the aspiring analyst and people who want to start from the beginning in any field needing this critical 21st-century skill.
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Gain new insights into your data. Learn to apply data science methods and techniques, and acquire analytical skills.
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Some easy resources from where beginners can start learning data science and its model for easy growth.
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Data Science is one of the career paths that we've seen the Bootcamp model successfully applied to over the past couple of years.
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Data science is a present-day technology world using a very common term. It is a multi-disciplinary entity that deals with data in a structured and unstructured manner.
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Become a Certified Programmer with some online courses without any efforts, just get a Professional degree with less cost.
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Real-time data visualization refers to visualization of data that is continuously updated as new data is generated by connected devices or people. This is the type of data that is used to make real-time decisions and, when done correctly, can truly transform business processes.
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Learn the fundamentals of computational mathematics and statistics, as well as some pseudocode being used today by data scientists and analysts.
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Apart from high-school and boardroom presentations, data visualization is used in a multitude of other places too. Where exactly - do you ask? Let us take a look at some of its major applications.
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The overall importance of data and information within organizations has continued to grow. We've also seen the continued rise of megatrends like IoT, big data - even too much data - and of course, machine learning.
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The demand for skilled data science practitioners is rapidly growing, and this series prepares you to tackle real-world data analysis challenges.
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First of all, it is important to understand that Machine Learning is basically a subset of Artificial Intelligence. ML is the process using which AI learns.
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Machine learning is one of the fastest-growing areas of computer science, with far-reaching applications.
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Data Visualization has become one of the common buzz phrases swirling around the internet these days.
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The demand for skilled data science practitioners is rapidly growing, and this series prepares you to tackle real-world data analysis challenges.
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Data science strategy for Dummies begins by explaining what exactly data science is and why it's important.
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The sets of raw facts and figures which are so complex and bulky that they cannot be dealt with using ordinary data processing software are called big data.
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These courses are perfect for true beginners, learn Python basics and start coding right away.
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As the analytics industry has grown over the years, it has given opportunities to companies to create tools that specifically cater to specific aspects of the data analytics procedures like data transformation, data formatting, visualization, etc.
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As the analytics industry has grown over the years, it has given opportunities to companies to create tools that specifically cater to specific aspects of the data analytics procedures like data transformation, data formatting, visualization, etc.
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Everybody has different opinions regarding big data. Some say it is just a phase that the tech world is going through and some say it is here for the long term.
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Firms use data science aggressively to be a market leader. Data is streaming in from different sources like web, social media, customer reviews, internal databases, and governmental datasets.
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This is a very simple post aimed at sparking interest in Data Analysis. It is by no means a complete guide, nor should it be used as complete facts or truths.
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Today, data science has turned into a revolutionary technology that is quite popular. Although many people want to become good data scientists, few know the pros and cons of it.
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Gain new insights into your data. Learn to apply data science methods and techniques, and acquire analytical skills.
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