Artificial Intelligence and machine learning

  What is machine learning? Everything you need to know Machine learning enables computers to deal with tasks that until now have been performed only by people. From driving cars to translation speeches, machine learning is driving an explosion in the capabilities of artificial intelligence - messy and unpredictable real-world experiences with the help of software. But what exactly is machine learning and what is the current boom in machine learning possible? What is machine Learning ? At a very high level, machine learning is the process of teaching a computer system how to accurately predict the data fed. Those predictions could be answered by whether a piece of fruit in a photo is a banana or an apple, with people crossing the road in front of a self-driving car, using the word book in a sentence that relates to a paperback Whether or not hotel reservation, whether an email is spam, or correctly identifies the speech to generate a caption for a YouTube video. The key differ...

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  Data Science Is Dead. Long Live Business Science : One can hardly call Data science scientific it can be considered as an unreliable friend.  so What to do with data science? It was observed that the way the media portray this profession is fundamentally wrong; data analyst do not just substitute data into ready-made algorithms 70 years’ history in 2 paragraphs and 1 picture. Data science can be classified as a  wide range of complex mathematical operations, and the most part of it was invented in the past but gained a second wind sue to the increasing use of significantly improved technical devices: increasing data day by day, more computing power, more reasonable results at a lower price. As the cost of storing and processing data went down, the volume of data collected each day went up: A simple law of supply & demand, or can be called the price elasticity of Data. The price goes down, the volume goes up. Someone will then have to do something with all this st...

   Burning Questions In Data Science : In every profession, there are disagreements between the members of the community. Most of the time, the quarrels happen either because both options are equally viable or there is very little evidence to prove one way or the other. And sometimes, people disagree just because they have different preferences and the choice is very subjective. Having an opinion on these disagreements is a neat cheat to look and feel like part of the community. Sooner or later you will be in the middle of these discussions anyways. I just want to give a small boost to this article. Python vs R You might have heard this discussion before you even started studying  data science . It is everywhere on the internet, everyone has something to say about it, and some people have very strong opinions on it. If you think caring about which language you use this much is silly then I’m with you. But it might just be one of the first things your colleagues ask you wh...

  Ten Trends Of IoT In 2020 : The Internet of Things (IoT) is actively shaping both the industrial and consumer worlds. Smart tech finds its way to every business and consumer domain there is — from retail to healthcare, from finances to logistics — and a missed opportunity strategically employed by a competitor can easily qualify as a long-term failure for companies who don’t innovate [3]. The year 2020 will hit all 4 components of IoT Model: Sensors, Networks (Communications), Analytics (Cloud), and Applications , with different degrees of impact. By 2020, the Internet of Things (IoT) is predicted to generate an additional $344B in revenues, as well as to drive $177B in cost reductions. IoT and smart devices are already increasing the performance metrics of major US-based factories. They are in the hands of employees, covering routine management issues and boosting their productivity by 40–60% [1]. The following 10 trends explore the impact of many technologies on IoT and pred...

  What Is CRISP – DM Methodology? CRISP - DM stands for Cross Industry Standard Process for Data Mining. The CRISP-DM methodology is practical, flexible and useful when solving business issues with analytics. The definition of CRISP – DM is a data mining technology or a methodology or a process that helps you or provides you a blueprint to conduct a data mining project. It was implemented in 1996 and was founded by major companies like Daimla Benz, ISL, NCR & OHRA. These companies have actually implemented in around 200 data mining users and tools and then they came up with this model. This is a non proprietory documented and freely available process that’s what the actually designed, so everybody can use it. How it helps? CRISP – DM provides a roadmap, it gives you best practices and it provides you structures for better and faster results of using data mining , so that’s how it helps the business to follow while planning and carrying out a data mining project. Read More : j...

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  8 Questions Which You Should Know Before Starting Data Science Career : It is all well and good to learn the technical skills that you need to become a d ata scientist . I think that it is also extremely important to learn to think like a data scientist . That means always questioning…basically everything Obviously every data science problem will require you to question your methods and the data in different ways, but there are a few things that I think are important to consider whenever embarking on any new data science project. In this story, I will go through those questions and why I think that they are important to be a responsible data scientist. My questions for any new data science project are: What is the question you are trying to answer? Do you know exactly what you are trying to measure? Do you have the right data to answer your question? Do you know enough about how your data was collected? Are there any ethical considerations? Who is going to read your analysis and...

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  How Artificial Intelligence Works? We have progressed from Stone Age to Space Age and are now rushing toward the age of artificial intelligence (AI). An age where, in layman’s terms, we will have substitutions for the human brain. An age where computers and robots will perform tasks that we perform today. There is an advancement of this technology at an alarming speed, especially in the West. At the same time, abundant data termed as ‘Big Data’ is being collected at an impossible rate. Even something as simple as liking a Facebook post sends information about you and that is why you would see similar posts and social media highly attuned to your likes and dislikes. This collection of data takes place on all platforms which makes the amount of data collected unimaginable. Read More  : Just click on this link

Artificial intelligence and Quality :  Know More : just click on this link

  How To Train Neural Network? As we know very well one of The most important parts of deep learning is training the  neural networks . So, let's learn how it actually works. In this article we will try to learn how a neural network gets to train. We will also learn about the feed-forward method and back propagation method in  Deep Learning . Why training is needed? Training in deep learning is the process that helps machines to learn about the function/equation. We have to find the optimal values of the weights of a neural network to get the desired output. To train a neural network, we use the iterative method using gradient descent. Initially we start with random initialisation of the weights. After random initialisation of the weights, we make predictions on the data with the help of forward-propagation method, then we compute the corresponding cost function  C , or loss and update each weight  w  by an amount proportional to  dC/dw , i.e., the der...

  What Is The Use Of Artificial Intelligence In Future? In the previous article we saw how Artificial Intelligence works so now moving further we will look upon what is the use of Artificial Intelligence in our future and in which areas will Artificial Intelligence impact our lives in future. Artificial Intelligence is definitely the future of the world. Artificial Intelligence will drive the economy of tomorrow. Are you excited about Artificial Intelligence? Google, Facebook, Apple, Microsoft are all moving ahead at great speed in improving this Artificial Intelligence . So, it’s very exciting! Software is going to solve that where it’ll look at the new information and present to you knowing about your interests what would be most valuable. So: making us more efficient. We’re focusing on autonomous systems and we sort of see it has the mother of all AI projects. Areas  where Artificial Intelligence is going to impact our future lives. Autonomous Transportation: As the com...

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  AI With Python – Computer Vision Computer vision is concerned with modeling and replicating human vision using computer software and hardware. In this chapter, you will learn in detail about this. Computer Vision Computer vision is a discipline that studies how to reconstruct, interrupt, and understand a 3d scene from its 2d images, in terms of the properties of the structure present in the scene. Computer Vision Hierarchy Computer vision is divided into three basic categories as following − Low-level vision  − It includes process images for feature extraction. Intermediate-level vision  − It includes object recognition and 3D scene interpretation High-level vision  − It includes a conceptual description of a scene like activity, intention, and behavior. Know More : just click on this link

  Artificial Intelligence With Python In this section, we will centre rational programming and how it helps in Artificial Intelligence. We definitely realise that rationale is the investigation of standards of right-thinking or in straightforward words, it is the investigation of what comes after what. For instance, in the event that two articulations are valid, at that point we can induce any third explanation from it. Idea Rationale Programming is the blend of two words, rationale, and programming. Rationale Programming is a programming worldview in which the issues are communicated as realities and rules by program proclamations however inside an arrangement of formal rationale. Much the same as other programming ideal models like item situated, useful, revelatory, and procedural, and so on., it is likewise a specific method to move toward programming. Read More : just click on this link 

  AI With Python – Gaming Games are played with a strategy. Every player or team would make a strategy before starting the game and they have to change or build a new strategy according to the current situation(s) in the game. Know More : Just click on this link.

  How To Explain Machine Learning Model In Interview : In preparation for any interview, I wanted to share a resource that provides brief descriptions of machine learning models . They are not meant to be comprehensive, but vice versa. Hopefully, by reading this, you will realize how you can communicate complex models in a simple way. Models Covered Linear Regression Ridge Regression Lasso Regression Logistic Regression K Nearest-Neighbours Naive Bayes Support Vector Machines Decision Trees Random Forests AdaBoost Gradient Boost XGBoost     Know More : Just click on this link