Edward Jackson

Edward Jackson

1550705036

Machine Learning: How to go from Zero to Hero

If your understanding of A.I. and Machine Learning is a big question mark, then this is the blog post for you. Here, I gradually increase your _Awesomenessicity_™ by gluing inspirational videos together with friendly text.

Sit down and relax. These videos take time, and if they don’t inspire you to continue to the next section, fair enough.

However, if you find yourself at the bottom of this article, you’ve earned your well-rounded knowledge and passion for this new world. Where you go from there is up to you.

Understanding Why Machine Learning is so HOT Right Now

A.I. was always cool, from moving a paddle in Pong to lighting you up with combos in Street Fighter.

A.I. has always revolved around a programmer’s functional guess at how something should behave. Fun, but programmers aren’t always gifted in programming A.I. as we often see. Just Google “epic game fails” to see glitches in A.I., physics, and sometimes even experienced human players.

Wow! Right?That’s a crazy process!

Now how is it that we can’t even understand the algorithm when it’s done? One great visual was when the A.I. was written to beat Mario games. As a human, we all understand how to play a side-scroller, but identifying the predictive strategy of the resulting A.I. is insane.

Impressed? There’s something amazing about this idea, right? The only problem is we don’t know Machine Learning, and we don’t know how to hook it up to video games.

Fortunately for you, Elon Musk already provided a non-profit company to do the latter. Yes, in a dozen lines of code you can hook up any A.I. you want to countless games/tasks! Check it out in action!

Why Should You Use Machine Learning?

I have two good answers on why you should care. Firstly, Machine Learning (ML) is making computers do things that we’ve never made computers do before. If you want to do something new, not just new to you, but to the world, you can do it with ML.

Secondly, if you don’t influence the world, the world will influence you.

Right now significant companies are investing in ML, and we’re already seeing it change the world. Thought-leaders are warning that we can’t let this new age of algorithms exist outside of the public eye. Imagine if a few corporate monoliths controlled the Internet. If we don’t take up arms, the science won’t be ours. I think Christian Heilmann said it best in his talk on ML.

“We can hope that others use this power only for good. I — for one, don’t consider this a good bet. I’d rather play and be part of this revolution. And so can you.”### OK, now I’m interested…

The concept is useful and cool. We understand it at a high level, but what the heck is actually happening? How does this work?

If you want to jump straight in, I suggest you skip this section and move on to the next “How Do I Get Started” section. If you’re motivated to be a DOer in ML, you won’t need these videos.

If you’re still trying to grasp how this could even be a thing, the following video is perfect for walking you through the logic, using the classic ML problem of handwriting.

Pretty cool huh? That video shows that each layer gets simpler rather than more complicated. Like the function is chewing data into smaller pieces that end in an abstract concept. You can get your hands dirty in interacting with this process on this site (by Adam Harley).

It’s cool watching data go through a trained model, but you can even watch your neural network get trained.

One of the classic real-world examples of Machine Learning in action is the iris data set from 1936. In a presentation I attended by JavaFXpert’s overview on Machine Learning, I learned how you can use his tool to visualize the adjustment and back propagation of weights to neurons on a neural network. You get to watch it train the neural model!

Even if you’re not a Java buff, the presentation Jim gives on all things Machine Learning is a pretty cool 1.5+ hour introduction into ML concepts, which includes more info on many of the examples above.

These concepts are exciting! Are you ready to be the Einstein of this new era? Breakthroughs are happening every day, so get started now.

How do I get started?

There are tons of resources available. First, you should subscribe to some newsletters/twitter accounts to keep the personal hype train rolling. I started this one!

As for “in-depth learning”, I’ll be recommending two approaches.

Nuts n Bolts

In this approach, you’ll understand Machine Learning down to the algorithms and the math. I know this way sounds tough, but how cool would it be to really get into the details and code this stuff from scratch!

If you want to be a force in ML, and hold your own in deep conversations, then this is the route for you.

I recommend that you try out Brilliant.org’s app (always great for any science lover) and take the Artificial Neural Network course. This course has no time limits and helps you learn ML while killing time in line on your phone.

This one costs money after Level 1.

Combine the above with simultaneous enrollment in Andrew Ng’s Stanford course on “Machine Learning in 11 weeks”. This is the course that Jim Weaver recommended in his video above. I’ve also had this course independently suggested to me by Jen Looper.

Everyone provides a caveat that this course is tough. For some of you that’s a show stopper, but for others, that’s why you’re going to put yourself through it and collect a certificate saying you did.

This course is 100% free. You only have to pay for a certificate if you want one.

With those two courses, you’ll have a LOT of work to do. Everyone should be impressed if you make it through because that’s not simple.

But more so, if you do make it through, you’ll have a deep understanding of the implementation of Machine Learning that will catapult you into successfully applying it in new and world-changing ways.

Speed Racer

If you’re not interested in writing the algorithms, but you want to use them to create the next breathtaking website/app, you should jump into TensorFlow and the crash course.

TensorFlow is the de facto open-source software library for machine learning. It can be used in countless ways and even with JavaScript. Here’s a crash course.

Plenty more information on available courses and rankings can be found here.

If taking a course is not your style, you’re still in luck. You don’t have to learn the nitty-gritty of ML in order to use it today. You can efficiently utilize ML as a service in many ways with tech giants who have trained models ready.

I would still caution you that there’s no guarantee that your data is safe or even yours, but the offerings of services for ML are quite attractive!

Using an ML service might be the best solution for you if you’re excited and able to upload your data to Amazon/Microsoft/Google. I like to think of these services as a gateway drug to advanced ML. Either way, it’s good to get started now.

UPDATES!

Here are some awesome tutorials I’ve found which you should check out

Let’s Be Creators

I have to say thank you to all the aforementioned people and videos. They were my inspiration to get started, and though I’m still a newb in the ML world, I’m happy to light the path for others as we embrace this awe-inspiring age we find ourselves in.

It’s imperative to reach out and connect with people if you take up learning this craft. Without friendly faces, answers, and sounding boards, anything can be hard. Just being able to ask and get a response is a game changer. Add me, and add the people mentioned above. Friendly people with friendly advice helps!

See?

I hope this article has inspired you and those around you to learn ML! I also would love for you to join me in finding cool and fun ML code. Star, watch, and contribute to my repo here: https://github.com/GantMan/fun-machine-learing

#machine-learning #data-science

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Buddha Community

Machine Learning: How to go from Zero to Hero

Elthel Mario

1550714698

thanks

sophia tondon

sophia tondon

1620898103

5 Latest Technology Trends of Machine Learning for 2021

Check out the 5 latest technologies of machine learning trends to boost business growth in 2021 by considering the best version of digital development tools. It is the right time to accelerate user experience by bringing advancement in their lifestyle.

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Visit Blog- https://www.xplace.com/article/8743

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Nora Joy

1604154094

Hire Machine Learning Developers in India

Hire machine learning developers in India ,DxMinds Technologies is the best product engineering company in India making innovative solutions using Machine learning and deep learning. We are among the best to hire machine learning experts in India work in different industry domains like Healthcare retail, banking and finance ,oil and gas, ecommerce, telecommunication ,FMCG, fashion etc.
**
Services**
Product Engineering & Development
Re-engineering
Maintenance / Support / Sustenance
Integration / Data Management
QA & Automation
Reach us 917483546629

Hire machine learning developers in India ,DxMinds Technologies is the best product engineering company in India making innovative solutions using Machine learning and deep learning. We are among the best to hire machine learning experts in India work in different industry domains like Healthcare retail, banking and finance ,oil and gas, ecommerce, telecommunication ,FMCG, fashion etc.

Services

Product Engineering & Development

Re-engineering

Maintenance / Support / Sustenance

Integration / Data Management

QA & Automation

Reach us 917483546629

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Nora Joy

1607006620

Applications of machine learning in different industry domains

Machine learning applications are a staple of modern business in this digital age as they allow them to perform tasks on a scale and scope previously impossible to accomplish.Businesses from different domains realize the importance of incorporating machine learning in business processes.Today this trending technology transforming almost every single industry ,business from different industry domains hire dedicated machine learning developers for skyrocket the business growth.Following are the applications of machine learning in different industry domains.

Transportation industry

Machine learning is one of the technologies that have already begun their promising marks in the transportation industry.Autonomous Vehicles,Smartphone Apps,Traffic Management Solutions,Law Enforcement,Passenger Transportation etc are the applications of AI and ML in the transportation industry.Following challenges in the transportation industry can be solved by machine learning and Artificial Intelligence.

  • ML and AI can offer high security in the transportation industry.
  • It offers high reliability of their services or vehicles.
  • The adoption of this technology in the transportation industry can increase the efficiency of the service.
  • In the transportation industry ML helps scientists and engineers come up with far more environmentally sustainable methods for powering and operating vehicles and machinery for travel and transport.

Healthcare industry

Technology-enabled smart healthcare is the latest trend in the healthcare industry. Different areas of healthcare, such as patient care, medical records, billing, alternative models of staffing, IP capitalization, smart healthcare, and administrative and supply cost reduction. Hire dedicated machine learning developers for any of the following applications.

  • Identifying Diseases and Diagnosis
  • Drug Discovery and Manufacturing
  • Medical Imaging Diagnosis
  • Personalized Medicine
  • Machine Learning-based Behavioral Modification
  • Smart Health Records
  • Clinical Trial and Research
  • Better Radiotherapy
  • Crowdsourced Data Collection
  • Outbreak Prediction

**
Finance industry**

In financial industries organizations like banks, fintech, regulators and insurance are Adopting machine learning to improve their facilities.Following are the use cases of machine learning in finance.

  • Fraud prevention
  • Risk management
  • Investment predictions
  • Customer service
  • Digital assistants
  • Marketing
  • Network security
  • Loan underwriting
  • Algorithmic trading
  • Process automation
  • Document interpretation
  • Content creation
  • Trade settlements
  • Money-laundering prevention
  • Custom machine learning solutions

Education industry

Education industry is one of the industries which is investing in machine learning as it offers more efficient and easierlearning.AdaptiveLearning,IncreasingEfficiency,Learning Analytics,Predictive Analytics,Personalized Learning,Evaluating Assessments etc are the applications of machine learning in the education industry.

Outsource your machine learning solution to India,India is the best outsourcing destination offering best in class high performing tasks at an affordable price.Business** hire dedicated machine learning developers in India for making your machine learning app idea into reality.
**
Future of machine learning

Continuous technological advances are bound to hit the field of machine learning, which will shape the future of machine learning as an intensively evolving language.

  • Improved Unsupervised Algorithms
  • Increased Adoption of Quantum Computing
  • Enhanced Personalization
  • Improved Cognitive Services
  • Rise of Robots

**Conclusion
**
Today most of the business from different industries are hire machine learning developers in India and achieve their business goals. This technology may have multiple applications, and, interestingly, it hasn’t even started yet but having taken such a massive leap, it also opens up so many possibilities in the existing business models in such a short period of time. There is no question that the increase of machine learning also brings the demand for mobile apps, so most companies and agencies employ Android developers and hire iOS developers to incorporate machine learning features into them.

#hire machine learning developers in india #hire dedicated machine learning developers in india #hire machine learning programmers in india #hire machine learning programmers #hire dedicated machine learning developers #hire machine learning developers

Nora Joy

1607006620

Hire Machine Learning Developer | Hire ML Experts in India

Machine learning applications are a staple of modern business in this digital age as they allow them to perform tasks on a scale and scope previously impossible to accomplish.Businesses from different domains realize the importance of incorporating machine learning in business processes.Today this trending technology transforming almost every single industry ,business from different industry domains hire dedicated machine learning developers for skyrocket the business growth.Following are the applications of machine learning in different industry domains.

Transportation industry

Machine learning is one of the technologies that have already begun their promising marks in the transportation industry.Autonomous Vehicles,Smartphone Apps,Traffic Management Solutions,Law Enforcement,Passenger Transportation etc are the applications of AI and ML in the transportation industry.Following challenges in the transportation industry can be solved by machine learning and Artificial Intelligence.

  • ML and AI can offer high security in the transportation industry.
  • It offers high reliability of their services or vehicles.
  • The adoption of this technology in the transportation industry can increase the efficiency of the service.
  • In the transportation industry ML helps scientists and engineers come up with far more environmentally sustainable methods for powering and operating vehicles and machinery for travel and transport.

Healthcare industry

Technology-enabled smart healthcare is the latest trend in the healthcare industry. Different areas of healthcare, such as patient care, medical records, billing, alternative models of staffing, IP capitalization, smart healthcare, and administrative and supply cost reduction. Hire dedicated machine learning developers for any of the following applications.

  • Identifying Diseases and Diagnosis
  • Drug Discovery and Manufacturing
  • Medical Imaging Diagnosis
  • Personalized Medicine
  • Machine Learning-based Behavioral Modification
  • Smart Health Records
  • Clinical Trial and Research
  • Better Radiotherapy
  • Crowdsourced Data Collection
  • Outbreak Prediction

**
Finance industry**

In financial industries organizations like banks, fintech, regulators and insurance are Adopting machine learning to improve their facilities.Following are the use cases of machine learning in finance.

  • Fraud prevention
  • Risk management
  • Investment predictions
  • Customer service
  • Digital assistants
  • Marketing
  • Network security
  • Loan underwriting
  • Algorithmic trading
  • Process automation
  • Document interpretation
  • Content creation
  • Trade settlements
  • Money-laundering prevention
  • Custom machine learning solutions

Education industry

Education industry is one of the industries which is investing in machine learning as it offers more efficient and easierlearning.AdaptiveLearning,IncreasingEfficiency,Learning Analytics,Predictive Analytics,Personalized Learning,Evaluating Assessments etc are the applications of machine learning in the education industry.

Outsource your machine learning solution to India,India is the best outsourcing destination offering best in class high performing tasks at an affordable price.Business** hire dedicated machine learning developers in India for making your machine learning app idea into reality.
**
Future of machine learning

Continuous technological advances are bound to hit the field of machine learning, which will shape the future of machine learning as an intensively evolving language.

  • Improved Unsupervised Algorithms
  • Increased Adoption of Quantum Computing
  • Enhanced Personalization
  • Improved Cognitive Services
  • Rise of Robots

**Conclusion
**
Today most of the business from different industries are hire machine learning developers in India and achieve their business goals. This technology may have multiple applications, and, interestingly, it hasn’t even started yet but having taken such a massive leap, it also opens up so many possibilities in the existing business models in such a short period of time. There is no question that the increase of machine learning also brings the demand for mobile apps, so most companies and agencies employ Android developers and hire iOS developers to incorporate machine learning features into them.

#hire machine learning developers in india #hire dedicated machine learning developers in india #hire machine learning programmers in india #hire machine learning programmers #hire dedicated machine learning developers #hire machine learning developers

Ananya Gupta

1595485129

Pros and Cons of Machine Learning Language

Amid all the promotion around Big Data, we continue hearing the expression “AI”. In addition to the fact that it offers a profitable vocation, it vows to tackle issues and advantage organizations by making expectations and helping them settle on better choices. In this blog, we will gain proficiency with the Advantages and Disadvantages of Machine Learning. As we will attempt to comprehend where to utilize it and where not to utilize Machine learning.

In this article, we discuss the Pros and Cons of Machine Learning.
Each coin has two faces, each face has its property and highlights. It’s an ideal opportunity to reveal the essence of ML. An extremely integral asset that holds the possibility to reform how things work.

Pros of Machine learning

  1. **Effectively recognizes patterns and examples **

AI can survey enormous volumes of information and find explicit patterns and examples that would not be evident to people. For example, for an online business site like Amazon, it serves to comprehend the perusing practices and buy chronicles of its clients to help oblige the correct items, arrangements, and updates pertinent to them. It utilizes the outcomes to uncover important promotions to them.

**Do you know the Applications of Machine Learning? **

  1. No human mediation required (mechanization)

With ML, you don’t have to keep an eye on the venture at all times. Since it implies enabling machines to learn, it lets them make forecasts and improve the calculations all alone. A typical case of this is hostile to infection programming projects; they figure out how to channel new dangers as they are perceived. ML is additionally acceptable at perceiving spam.

  1. **Constant Improvement **

As ML calculations gain understanding, they continue improving in precision and productivity. This lets them settle on better choices. Let’s assume you have to make a climate figure model. As the measure of information you have continues developing, your calculations figure out how to make increasingly exact expectations quicker.

  1. **Taking care of multi-dimensional and multi-assortment information **

AI calculations are acceptable at taking care of information that is multi-dimensional and multi-assortment, and they can do this in unique or unsure conditions. Key Difference Between Machine Learning and Artificial Intelligence

  1. **Wide Applications **

You could be an e-posterior or a social insurance supplier and make ML work for you. Where it applies, it holds the ability to help convey a considerably more close to home understanding to clients while additionally focusing on the correct clients.

**Cons of Machine Learning **

With every one of those points of interest to its effectiveness and ubiquity, Machine Learning isn’t great. The accompanying components serve to confine it:

1.** Information Acquisition**

AI requires monstrous informational indexes to prepare on, and these ought to be comprehensive/fair-minded, and of good quality. There can likewise be times where they should trust that new information will be created.

  1. **Time and Resources **

ML needs sufficient opportunity to allow the calculations to learn and grow enough to satisfy their motivation with a lot of precision and pertinence. It additionally needs monstrous assets to work. This can mean extra necessities of PC power for you.
**
Likewise, see the eventual fate of Machine Learning **

  1. **Understanding of Results **

Another significant test is the capacity to precisely decipher results produced by the calculations. You should likewise cautiously pick the calculations for your motivation.

  1. High mistake weakness

AI is self-governing yet exceptionally powerless to mistakes. Assume you train a calculation with informational indexes sufficiently little to not be comprehensive. You end up with one-sided expectations originating from a one-sided preparing set. This prompts unessential promotions being shown to clients. On account of ML, such botches can set off a chain of mistakes that can go undetected for extensive periods. What’s more, when they do get saw, it takes very some effort to perceive the wellspring of the issue, and significantly longer to address it.

**Conclusion: **

Subsequently, we have considered the Pros and Cons of Machine Learning. Likewise, this blog causes a person to comprehend why one needs to pick AI. While Machine Learning can be unimaginably ground-breaking when utilized in the correct manners and in the correct spots (where gigantic preparing informational indexes are accessible), it unquestionably isn’t for everybody. You may likewise prefer to peruse Deep Learning Vs Machine Learning.

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