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Artificial Intelligence And Machine Learning Group / Survey - People Interested In Artificial Intelligence And Machine Learning / Data Analysis And Machine Learning Using R (2) (3) (4)
Deep Learning And Machine Learning by osarenomaspecial: 7:01pm On Jan 08, 2016 |
please i want to learn deep learning and machine learning,where can i start from? somebody told me i have to be good in linear algebra,probability,multi and single variable calculus, statistics and programming. i need your help guys. those maths hard ooo. |
Re: Deep Learning And Machine Learning by GoodBoi1(m): 8:09pm On Jan 08, 2016 |
I have interest in machine learning too. Found this link https://darshanhegde./2014/08/19/learn-machine-learning-the-hard-way/ |
Re: Deep Learning And Machine Learning by osarenomaspecial: 8:24pm On Jan 08, 2016 |
thanks bro,have you started? |
Re: Deep Learning And Machine Learning by omohayek: 12:25pm On Jan 09, 2016 |
Instead of visiting some random blog, why not just look at the free course materials available on Coursera and EdX? https://www.coursera.org/learn/machine-learning https://courses.edx.org/courses/CaltechX/CS1156x/Fall2013/ https://www.coursera.org/course/neuralnets 2 Likes |
Re: Deep Learning And Machine Learning by Sundayademola(m): 3:49pm On Jan 09, 2016 |
Both are relatively easy to pick up, persistence and enthusiasm weed out the great from the good. I am into both and you can be specific about what you need. The mathematics is present (non-arguable), but they can be picked up once you start learning. Some of the things listed below will be helpful, 1. Don't give up easily, everything is really about tuning till you get the desired results. 2. Follow industry experts and professionals. (e.g Andrew Ng et al) 3. Do healthy competitions (e.g Kaggle.com) 4. Read a lot. 5. Apply Good luck and may the machines get smarter 3 Likes |
Re: Deep Learning And Machine Learning by talk2hb1(m): 4:49pm On Jan 09, 2016 |
osarenomaspecial:Try this free online course on Udacity but you need a background course in statistic. https://www.udacity.com/course/viewer#!/c-ud262/l-3625438937 (Machine Learning) https://www.udacity.com/course/viewer#!/c-st101 (Statistic Course) Regards' Habeeb Salam |
Re: Deep Learning And Machine Learning by anthropino: 8:44pm On Jul 25, 2016 |
I am not a usual user here. But this subject seems about education. I think I can add some things. First it depends on the level at which you want to learn machine learning. But I assume you want to do interesting things with it---not petty studies 1) Statistics and probability are of course a requirement. Probability,random variables and stochasic processes. Athanasious Papoulis (up to the chapter on statochastic process) Statistics for Mathematicians by Victor Panaretos Principles of functional analysis Rudin Walter A first look at rigorous probability theory Jeffrey Rosentha (this is if you have the time) This is a video on " Statistical machine learning from stanford and the books are free" Use these to reinforce your knowledge. https://lagunita.stanford.edu/courses/HumanitiesSciences/StatLearning/Winter2016/about http://www-bcf.usc.edu/~gareth/ISL/ These text books cover much of the mathematical requirement. These are not really hard! It takes time, I mean even years to *master all. So dont be harsh on yourself. Nobody is an inherent genius--- you only become genius when you do and think about it for a long time---hence and thats what you what your machines to learn to achieve. *****(I must say I am bias towards Math and forgive me for this)More importantly you have to solve exercises in the books I have listed.Get the solution manual and solve at least 2 to 3 questions per chapter. If you are getting rusty on your math ---thats normal...just relearn your stuffs and you are good. Start from calculus --see recommendation below--- and go to linear algebra, functional analysis, probability/statistics, and machine learning. For multivariate calculus you dont need to know the whole concept , you will only get to use only some of the theorems. 2) Python Machine learning by Sebastian will give you hands on idea about the topic of machine learning (The book uses python which is very easy to learn). 3) Pattern recognition and machine learning Bishop (this is somehow the bible of machine learning) Then there are few courses on coursera and edx as mentioned by others (Machine learning specialisation , Machine learning by Andrew Ng, and the last from Caltech) As I said this is if you want rigorous stuff. Otherwise just read the book (2) and get your hands dirty. Thanks, Happy reading. NB: If you need to brush up your calculus and linear algebra . Here is what I recommend: Caculus 1A,B,C from MIT (I should say that this is not about trying to solve differentiation but understanding the subtle genesis of the concept and see the picture clearly in your mind. With this I bet you there is no where you would go that you wont say you understand calculus --at least at a good level) https://www.edx.org/course/calculus-1a-differentiation-mitx-18-01-1x For Multivariable calculus . check vector calculus by Marsden. or the OCW MIt course on multivariable calculus For linear algebra straight away go for Linear Algebra and its application by Gilbert! For programming : don't worry once you get your hands dirty with the book you will learn a lot of machine learning algorithm. But feel free to to MIT OCW python programming course (I assume you will be using python for start--- or you can change to any language of your choice__Especially any language you already know. ********Lastly after working this hard, ask yourself what can you do with machine learning . How do I monetize my ideas? Of course you can go for computer vision, robotics and data analytics and other applied areas ! May be even machine learning algorithm for Nairaland! 2 Likes 1 Share |
Re: Deep Learning And Machine Learning by abubaka101: 10:40pm On Jul 25, 2016 |
For starters, I recommend this book: Programming Collective Intelligence: Building Smart Web 2.0 Applications by Toby Segaran. It'll get you started on the concepts, algorithms and even converting theory to code. 3 Likes 1 Share |
Re: Deep Learning And Machine Learning by talk2hb1(m): 11:12pm On Jul 26, 2016 |
abubaka101:If anybody wants' it should contact me here... |
Re: Deep Learning And Machine Learning by Scholar8200(m): 6:50pm On Apr 21, 2017 |
talk2hb1:hello, I am interested. How much is it? |
Re: Deep Learning And Machine Learning by Nobody: 5:35pm On May 04, 2017 |
osarenomaspecial: So, how far have you gone? |
Re: Deep Learning And Machine Learning by itzLanreY: 6:16pm On Sep 01, 2018 |
talk2hb1: Good..I'm also interested in machine learning and artificial intelligence,But what are the job opportunities of a machine learning expert especially in Nigeria? |
Re: Deep Learning And Machine Learning by Nobody: 6:00am On Sep 02, 2018 |
osarenomaspecial: Before you jump into Deep Learning yakata learn about other machine learning algorithms e.g naive Bayes and the rest. |
Re: Deep Learning And Machine Learning by Nobody: 6:04am On Sep 02, 2018 |
My own problem sef is the mathematical notations that are hard to read and understand from those theoretical books like "The Elements of Statistical Learning " and Bishop's book. If I could just understand them..... |
Re: Deep Learning And Machine Learning by Olalekank(m): 9:08pm On Sep 02, 2018 |
One of the materials I've seen and loved is Introduction to machine learning on udacity. Me loving it doesn't mean it's the best. |
Re: Deep Learning And Machine Learning by Nobody: 6:38am On Sep 04, 2018 |
You guys should stop derailing this thread with your shitty ads! |
Re: Deep Learning And Machine Learning by udy01(m): 7:10am On Sep 04, 2018 |
Pls good
naija youth i need the activation code
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collection. thanks God bless |
Re: Deep Learning And Machine Learning by dubanib: 2:57pm On Sep 05, 2018 |
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Re: Deep Learning And Machine Learning by Myriad1: 11:26am On Jun 23, 2022 |
Can I have your digit . |
Re: Deep Learning And Machine Learning by mrainm: 1:36pm On Mar 12, 2024 |
The development of deep learning and machine learning https://servreality.com/machine-learning/ opens up broad prospects in various fields. These technologies make it possible to create intelligent systems capable of processing large amounts of data, recognizing images, predicting trends, and making automated decisions. In medicine, finance, science, and other fields, deep learning and machine learning open new opportunities to optimize processes, improve efficiency, and achieve innovation. |
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