20 Best Machine Learning Books for bigginers and experts

1. The Hundred-Page Machine Learning Book

Topics covered
Anatomy of a learning algorithm
Fundamental algorithms
Neural networks and deep learning
Other forms of learning
Supervised learning and unsupervised learning

2. Programming Collective Intelligence: Building Smart Web 2.0 Applications

Topics covered
Bayesian filtering
Collaborative filtering techniques
Evolving intelligence for problem-solving
Methods for detecting groups or patterns
Non-negative matrix factorization
Search engine algorithms
Support vector machines
Ways to make predictions

3. Machine Learning for Hackers: Case Studies and Algorithms to Get you Started

Topics covered
Developing a naïve Bayesian classifier
Linear regression
Optimization techniques
Using R for querying data

4. Machine Learning

Topics covered
Genetic algorithms
Inductive logic programming
Introduction to primary approaches to machine learning
Machine learning concepts and techniques
Re-enforcement learning

5. The Elements of Statistical Learning: Data Mining, Inference, and Prediction

Topics covered
Ensemble learning
High-dimensional problems
Linear methods for classification and regression
Model inference and averaging
Neural networks
Random forests
Supervised and unsupervised learning

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Robotics. What is Robotics? What are Robots? Types & Uses of Robots.

Robotics Technology

Robotics is an interdisciplinary sector of science and engineering dedicated to the design, construction and use of mechanical robots. Our guide will give you a concrete grasp of robotics, including different types of robots and how they're being applied across industries.
What Is Robotics?

Robotics is the intersection of science, engineering and technology that produces machines, called robots, that substitute for (or replicate) human actions. Pop culture has always been fascinated with robots. R2-D2. Optimus Prime. WALL-E. These over-exaggerated, humanoid concepts of robots usually seem like a caricature of the real thing...or are they more forward thinking than we realize? Robots are gaining intellectual and mechanical capabilities that don’t put the possibility of a R2-D2-like machine out of reach in the future.

As technology progresses, so too does the scope of what is considered robotics. In 2005, 90% of all robots could be found assembling cars in automotive factories. These robots consist mainly of mechanical arms tasked with welding or screwing on certain parts of a car. Today, we’re seeing an evolved and expanded definition of robotics that includes the development, creation and use of bots that explore Earth’s harshest conditions, robots that assist law-enforcement and even robots that assist in almost every facet of healthcare.

While the overall world of robotics is expanding, a robot has some consistent characteristics:
Robots all consist of some sort of mechanical construction. The mechanical aspect of a robot helps it complete tasks in the environment for which it’s designed. For example, the Mars 2020 Rover’s wheels are individually motorized and made of titanium tubing that help it firmly grip the harsh terrain of the red planet.
Robots need electrical components that control and power the machinery. Essentially, an electric current (a battery, for example) is needed to power a large majority of robots.
Robots contain at least some level of computer programming. Without a set of code telling it what to do, a robot would just be another piece of simple machinery. Inserting a program into a robot gives it the ability to know when and how to carry out a task.

We’re really bound to see the promise of the robotics industry sooner, rather than later, as artificial intelligence and software also continue to progress. In the near future, thanks to advances in these technologies, robots will continue getting smarter, more flexible and more energy efficient. They’ll also continue to be a main focal point in smart factories, where they’ll take on more difficult challenges and help to secure global supply chains.

Though relatively young, the robotics industry is filled with an admirable promise of progress that science fiction could once only dream about. From the deepest depths of our oceans to thousands of miles in outer space, robots will be found performing tasks that humans couldn’t dream of achieving alone.

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China’s ‘Mind-Boggling’ Claims – New AI System Can Design Hypersonic Weapons By Itself Without Human Intervention

Although the United States remains the world leader in anti-submarine warfare and artificial intelligence, China's efforts to harness "quality data" for military use have put Beijing far ahead of the Pentagon, according to a former US Navy admiral.

According to a new paper published in a journal run by China's aerospace defense industry, Beijing has made significant progress toward developing an AI (artificial intelligence) system capable of designing new hypersonic weapons autonomously.

“It was frustrating for all of us working with large excel spreadsheets, in deciding which programs to advance and which to curb”, said Admiral Bill Moran (retired), a former Vice Chief of US Naval Operations, while speaking at a Navy League webinar on artificial intelligence in November 2021.

On March 16, a team of researchers led by Professor Le Jialing with China Aerodynamics Research and Development Centre in Mianyang, Sichuan, published their findings in the Journal of Propulsion Technology.

Le has been an advisor to the Chinese military on hypersonic weapon technology for more than three decades, according to the publicly available information.

As hypersonic research in China advances to Mach 8 – eight times the speed of sound – and above, the volume of experimental data to be processed and analyzed has also been increasing significantly, researchers say.


In such a situation, the human brain can no longer keep up with the rapid pace of hypersonic technology development according to Le and his team.

Countries across the world are racing to achieve hypersonic flight capability and an essential part of this race are simulation experiments that virtually create extreme hypersonic flight conditions in ‘wind tunnels’.

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DATA SCIENCE ACTS AS A TRIGGER TO BOOST BUSINESS GROWTH

 Data science and business expansion

Data is important, as is the science involved in translating it. Millions of bytes of information are created each day, and its value has recently surpassed that of oil. A data scientist's role is and will continue to be critical for businesses in a variety of industries.

Data science is important for businesses because it has revealed amazing arrangements and intelligent decisions in a variety of industry verticals. The incredible approach of using intelligent machines to stir massive amounts of data to comprehend and investigate behaviour and examples is absolutely amazing. To that end, data has received all of the attention. Big Data can help you "predict" your requirements ahead of time, resulting in better client support outcomes.

There are numerous ways by which Data Science is assisting businesses with running in a superior manner:

1. Business Intelligence for Making Smarter Decisions – With the gigantic expansion in the volume of information, business needs data scientists to investigate and get significant experiences from the information. Data has delivered Business Intelligence to join a wide scope of business tasks. The significant experiences will help the data science organizations to examine data at an enormous scope and gain important dynamic methodologies.

2. Improving Products – Industries expect data to foster items that suit the prerequisites of clients and furnish them with ensured fulfillment. The cycle includes the examination of client audits to track down the best fit for the items. This investigation is done with the high-level logical devices of Data. Industries use the current market patterns to devise an item for the general population.

3. Overseeing Businesses Efficiently – Businesses today are data-rich. They have plenty of information that permits them to acquire experiences through a legitimate investigation of the information. Data Science stages uncover the secret examples that are available inside the data and help to make significant investigation and forecast of occasions. Huge scope organizations and few new companies can profit from data science.

4. Mechanizing Recruitment Processes – Data Science plays a vital influence in carrying computerization to a few enterprises. Data advancements like picture acknowledgment can change over the visual data from the resume into a computerized design. It then processes the data utilizing different scientific calculations like grouping and arrangement to produce the right contender, to get everything taken care of.

Data Science and Artificial Intelligence are significantly affecting business and are quickly becoming basic for separation and sometimes for endurance. Data can increase the value of any business that can utilize its data well. From measurements and experiences across work processes and employing new competitors, to assisting ranking staff with settling on better-informed choices, data science is significant to any organization in any industry.

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Different Emerging Technologies in Data Science

The landscape of business today is in a constant state of change, and data science makes a significant impact on the industry. As human interaction with technology grows by the day, the amount of data that is generated on a routine basis is immeasurable. This data is found in the raw form and is of immense value to business and research.


Emerging technologies in Data Science

As a developing field, data science has an enormous scope to grow larger. The latest discoveries and trends have set it apart from major professions in ways more than one. To understand the opportunities this field holds, one must understand the emerging technologies in data science that are shaping the future, and for the better.

1. Artificial Intelligence

2. Cloud Services

3. AR/VR Systems

4. IoT

5. Big Data

6. Automated Machine Learning

7. Quantum Computing

8. Digital Twins

Bottomline

Data science is set to take the world by storm and reach new milestones as more and more companies are realizing how important data is for their business growth and success. With the help of technology such as Artificial Intelligence (AI) and quantum computing, the coming years are going to be eventful for data scientists, businesses, and their customers alike, as many discoveries and developments await. This profession is not bound to see a decline anytime soon. Moreover, it will change the way you interact with technology and provide a competitive edge to the business that adopts it. That can only mean one thing – enhanced business success and higher customer satisfaction.

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Top 10 Machine Learning Project Ideas That You Can Implement

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Machine Learning is one of the most popular emerging technologies in current times! 

And the best way to learn this technology is by doing projects.

1. Titanic Survival Project

This is a beginner’s project on Kaggle that is best for you if you are just getting started with ML projects. This deals with the Titanic disaster that is one of the most famous in marine history. All you have to do in the project is predict which passengers survived the Titanic shipwreck based on data such as their age, gender, socio-economic class, etc. For example, it is highly probable that someone rich from the first-class survived as compared to someone from the third class. You can use the Titanic dataset on Kaggle for this project. And just to make things more interesting, this dataset contains real data based on the people who died and survived the actual Titanic disaster.

2. Personality Prediction Project

Imagine how interesting it would be to read the posts written by people online and be able to understand their overall personality? It would solve a lot of confusion on the internet! This ML project aims to find the Myers Briggs personality of a person based on the types of posts they put on social media. Myers Briggs Type Indicator is a personality identification system that divides a person into one of 16 different personalities based on introversion, intuition, thinking, and perceiving capabilities. The axis ranges from Introversion (I) to Extroversion (E), Intuition (N) to Sensing (S), Thinking (T) to Feeling (F), and Judging (J) to Perceiving (P).

3. Loan Prediction Project

It’s not at all easy to get a loan from the bank. Getting a loan approved requires a complex mix of factors not the least of which is a steady income! So this ML project aims to create a model that will classify how much loan the user can obtain based on various factors such as the user’s marital status, income, education, employment prospects, number of dependents, etc. The Loan prediction data set provides details about all these factors which can then be used to create an ML model that demonstrates the amount of loan that can be approved.

4. Stock Price Prediction Project

5. Xbox Game Prediction Project

6. Housing Prices Prediction Project

7. Sales Prediction Project

8. Digit Recognizer Project

9. Credit Card Approval Prediction10. 

10. IMDB Box Office Prediction

Movies are a big part of our world! But nobody knows how a movie will perform at the box office. There are some bix budget movies that bomb and there are smaller movies that are smashing successes. This project tries to predict the overall worldwide box office revenue of movies using data such as the movie cast, crew, posters, plot keywords, budget, production companies, release dates, languages, and countries. The dataset on Kaggle contains all these data points that you can use to predict how a movie will fare at the box office.

All of these ML Project Ideas are great options if you are just starting in Machine Learning or if you know the basics and need more practice. So check out all of these projects and when you are done with them, you can attempt even more projects on Kaggle and also take part in the active competitions. Who knows, you might even win the first prize!

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Artificial neurons go quantum with photonic circuits

 (Quantum memristor as the missing link between artificial intelligence and quantum computing)

Artificial intelligence is now used in a variety of applications, 

including speech recognition, image recognition, medical diagnosis, 

and many others. Simultaneously, quantum technology has been demonstrated 

to be capable of computational power far exceeding that of even the world's largest supercomputer.

In recent years, artificial intelligence has become ubiquitous, with applications such as speech interpretation, image recognition, medical diagnosis, and many more. At the same time, quantum technology has been proven capable of computational power well beyond the reach of even the world's largest supercomputer. Physicists at the University of Vienna have now demonstrated a new device, called a quantum memristor, which may allow combining these two worlds, thus unlocking unprecedented capabilities. The experiment, carried out in collaboration with the National Research Council (CNR) and the Politecnico di Milano in Italy, has been realized on an integrated quantum processor operating on single photons. The work is published in the current issue of the journal Nature Photonics.

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Kerala police to get training in AI, Data Analytics

Synopsis

​​DUK Vice Chancellor Saji Gopinath said this programme marks the next level of e-Governance. 

This is the stage where we start optimizing the processes, 

making the government smart and predictive, or in other words, Intelligent, he said.

HIGHLIGHT : The training programme has 150 hours of classroom sessions that would be handled 

by industry experts and researchers. As many as 15 select officers from the police department 

would undergo the first batch of training, the statement added.

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