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## Chemoton § Vitorino Ramos’ research notebook

Well just a fortnight or so back I discovered that Dr Radford Neal, one of the top researchers in Statistics and Machine Learning was blogging. And today morning I discovered Dr Vitorino Ramos has been blogging for over a week now too!

This comes as a surprise, but a very pleasant one. I am very glad to have found his page, it promises to be a very different Web-Log and could indeed grow into one of the top blogs on Swarming, Self-Organization, Complexity and Distributed Systems as it would be by a leading expert in the field. It would be great to catch up on his work. In the past I have tried to write on some of his interesting work on my own page. My posts can be found here.

[Vitorino Ramos: Image Source]

Dr Ramos’ research areas are chiefly in Artificial Life, Artificial Intelligence, Bio-Inspired Computing, Collective Intelligence and Complex Systems. He obtained his PhD in 2004 and has published about 70 papers in the above fields and their broad application areas. So put simply it can be said that the IQ of the “blogosphere” has gone up a little with this addition.

For starters I would recommend his article on Financial Markets (given the situation today), talking about the herd mentality and the resulting amplification in dumb investors and its results and what it could result in. Most investors do not understand much of the market mechanism. This is a bare fact put most aptly in this cartoon I found on his blog, and his post goes much beyond that.

Click to Enlarge

And going by the website and blog name, it seems that Dr Ramos is now interested in some sense in Tibor Ganti’s Chemoton Theory.

2. Dr Ramos’ Publications. (PDFs available online)

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Some of the search queries that lead to this blog really amaze/ perplex/ puzzle me and sometimes even embarrass me. Though yes, sometimes the search queries are very smart! Following a post by Dr Aurelie Thiele that echoed the same sentiment (minus the embarrassment I guess), I decided to index some BASIC Google searching tips that I use frequently which I think could be of help. Even if you are using most of them or some of them you can add some which you have not been using often and also suggestions (for operators, not essentials) would be most welcome.

Google is by far the most popular search engine on the Internet, accounting for about 80 percent of all the search queries made on it. Google has become highly popular not only because of its searching abilities but also because of the vast number of querying options that it comes with. Obviously with so many functions most of us miss out on them, and some that we miss out on turn out to be really very helpful. Also with such powerful searching capabilities there is a very valid concern for privacy violations, as unsuspecting sites can keep out private information open for smart searches, but let’s not talk about that in this post. Maybe sometime later.

I will also not be talking about the various services that Google offers, though they can largely change the output of a particular search. I would leave that part out.

Basic Operators: + (Addition); (Subtraction); * (Multiplication); / (Division); % of (Percentage of); ^ (Raised to a Power).

Calculator Examples: Note the examples for some cool ones.

75% of 150;    12^13;    87 in hexadecimal;     (2+i)*(3+i);    the speed of light in knots;    m_moon;

r_saturn;    h;    kbit/s in bit/s;    40USD to RUR;    sqrt(-9);    200 pounds*780 feet in calories.

I would leave it on the reader to try more interesting queries taking ques from the above if they were of any help at all.

Other Essentials and search features and tips can be obtained from the page I linked to.

First thing to remember is that one should not search on Google thinking it understands human language. The main point is to search for key words and to search them using appropriate queries instead of asking Google a question. This “question” type of searching can work for simple questions such as “What is Dino?” However it is difficult to get good results if we are looking for more specific results.

Google Query Operators: Here I index some of the most commonly used and most useful query operators. Skillful use of such operators can lead to very interesting results that otherwise would have been rather elusive. These are common knowledge, but no harm in indexing them again I suppose?

1. site: This restricts the search results to sites within the specified domain;

Example: site:wikipedia.org vector will find all sites containing the word vector within the *.wikipedia.org domain.

2. intitle: This restricts results to only those which have the specified phrase or word in their title.

Example: intitle:Hilbert Space will find all sites containing the word Hilbert in the title and the word Space in the text.  Suppose you want to search for BOTH the words Hilbert and Space to be in the title then the search query would be intitle:Hilbert intitle:Space

3. allintitle: This is an equivalent of the above. A phrase following the operator “allintitle” would return results that would give all of them in the title.

4. inurl: This restricts the results to only those sites which contain this phrase in their URL.

Example: inurl:Hilbert Space will find all sites that have the phrase “Hilbert” in their URL and “Space” in the text. Again if we wish to have both the words “Hilbert” and “Space” in the URL then we can use the query inurl:Hilbert inurl:Space

5. allinurl: This is an equivalent of the above.

Example: allinurl:Hilbert Space will find out all the sites that have both the phrases “Hilbert” and “Space” in the URL.

6. filetype, ext: This operator returns results restricted to only documents of the specified type.

Example: filetype:pdf Voronoi will restrict the search results to only pdfs which have the phrase “Voronoi” in the text.

7. link: This operator returns all the sites that contain links to the specified site.

Example: link:www.mit.edu will return all sites in results that contain at least one link to http://www.mit.edu

8. numrange: This operator restricts the search results to documents containing numbers only within a specified range.

Example: numrange:1123-3452 Voronoi will restrict results to only those sites that contain a number in between 1123 and 3452 and ALSO contain the word “Voronoi” in the text.

9. inanchor: This operator restricts the results to websites that contain links with the specified phrase in their descriptions.

Example: inanchor:wildboar will return results with links whose descriptions contains the word wildboar.

10. allintext: This returns sites, documents with the specified phrase only in the document text and NOT in the URL, title or link description.

Example: allintext:”Weighted Regression” will return results that have the phrase “Weighted Regression” in their text.

11. safesearch: This returns sites containing the specified phrase without returning mature material.

12. define: This returns a list of definitions for the specified phrase.

Example: define: publish returns a list of definitions of the phrase “define”.

13. related: Returns results similar to the specified website.

Example: related:www.example.com returns results websites which are related to http://www.example.com

14. +: This returns results that will contain the phrase specified more frequently.

Example: +Onion will return results by the number of occurrences of the word “Onion”.

15. – : This returns results that will NOT contain the specified phrase.

Example: -Onion will return results that will not contain the word “Onion”.

16. “” : The quotes serve as delimiters for the search phrase. This will return results only containing the specified phrase.

Example: “Voronoi Analysis” will only return results that contains the phrase “Voronoi Analysis”.

17. . : The dot operator serves as a wild card for a SINGLE CHARACTER.

Example: Angry.Fox will return results containing the phrases “Angry Fox”, “Angry7Fox”,”Angry-fox”, “AngryXFox” and so on.

18. * : This serves as a wildcard for a word.

Example: Angry*Fox will return results having phrases such as Angry the fox, Angry A Fox, Angry Why Fox and so on.

19. | : Logical OR. Returns results that contain either of the two specified phrases.

Example: “Paul Erdos” | “Carl Sagan” will return results that contain either the phrase “Paul Erdos” or “Carl Sagan” or both.

The above was a brief list of some of the most basic query operators that can optimize search results very significantly.

There are many more queries that are suited only for advanced users. I will not index them here as I don’t think there is the need. I might provide them on email but only at my own discretion.  Feel free to e-mail me.

These Queries fall under the following categories:

1. Queries for locating Web-Servers.

2. Queries for locating standard post installation web server pages.

3. Queries for application generated system reports.

4. Queries for Error messages.

5. Queries for locating network devices.

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I started writing this post on 18 June with the singular aim of posting it by 22 June. The objective of this post was to celebrate the life and ideas of Tommy Gold (May 22, 1920 – June 22, 2004) on his fourth death anniversary. But after that I did not have much access to the Internet for reasons I had posted about earlier, and so sadly I missed that date. After that I did not edit and post it as I thought there would be little point. Now I think it is okay to  post it instead of deleting it all together. A tribute to Thomas Gold would still be the aim though I regret I could not post in time.

[Image Source]

Quoting Thomas Gold (Source):

New ideas in science are not always right just because they are new. Nor are the old ideas always wrong just because they are old. A critical attitude is clearly required of every scientist. But what is required is to be equally critical to the old ideas as to the new. Whenever the established ideas are accepted uncritically, but conflicting new evidence is brushed aside and not reported because it does not fit, then that particular science is in deep trouble – and it has happened quite often in the historical past. If we look over the history of science, there are very long periods when the uncritical acceptance of the established ideas was a real hindrance to the pursuit of the new. Our period is not going to be all that different in that respect, I regret to say.

This paragraph reminds me of a post on Gaping Void, a blog that I just discovered two days back on the fantastic Reasonable Deviations. The post, titled Good Ideas Have Lonely Childhoods is highly recommended to read, as a vast majority of good ideas are heretical and this post is on a heretic. Infact this post on Gaping Void prompted me to publish this forgotten draft!

Thomas Gold was a true renaissance man, a brilliant polymath and a controversial figure who Freeman Dyson has described as a modern heretic. Gold was born as an Austrian and was educated in Switzerland and the UK, Initially he worked with Hermann Bondi and Fred Hoyle and then later accepted an appointment with the prestigious Cornell University and remained there till his death.

Gold portrays the typical rebel scientist, with a penchant for controversy and working against general and strongly held theories. Gold worked across a large number of fields- Cosmology, Biophysics, Astrophysics, Geophysics, Space Engineering etc. Throughout his career Gold never cared about being wrong or of the opposition. He had this knack of turning out to be right. He however was not afraid to be wrong, infact he has been very famously wrong two times and he took both times in good humor. Such was his intellect that he never cared of any opposition and his ideas have always been very interesting. I hope to chronicle some of his major ideas here.

Coming back, as I said he has been famously wrong two times:

1. First was the steady state theory. Gold along with Fred Hoyle and Hermann Bondi developed and published the steady state theory of the universe in 1948. The three thought that it was impossible to think that all of matter could be created out of an initial singularity. The theory proposed that new matter is created continuously and this accounts for the constant density of the expanding universe. Though this seems to have violated the first law of thermodynamics the steady state had a number of supporters in the 50s and the 60s but the discovery of the cosmic background radiation which basically is a remnant of the big bang or explosion was the first major blow to it and over time its wide acceptance declined to only a very few cosmologists like Jayant V. Narlikar, who very recently have proposed alternatives and modifications to the original idea of steady state like the quasi steady state. However whatever said and done, the competition between the Big Bang and the Steady State spurred a lot of research which ultimately has helped us understand the cosmos better as good competition always does.

2. His second major incorrect idea was proposed in 1955, when he said that moon’s surface was covered with a fine rock powder that is electro-statically supported. He later said that astronauts would sink as soon as they landed on the moon. His theory influenced the design of the American Surveyor lunar landing probes to a very large extent. But their precautions were excessive and most of the fears were unfounded, though when the Apollo 11 crew bought back soil samples from the moon, it was indeed powdery though nowhere close to the extent Gold had proposed it to be. However a lot of astronomers credit a lot of development in planetology in subsequent years to Gold’s initial work and ideas on the lunar regolith.

[The famous photo of the footprint on the Lunar Surface: The Lunar soil was powdery as predicted by Gold but nowhere to the extent he had thought so. Image Source : Wikipedia Commons]

On both the occasions Gold took “defeat” in good humor, the trademark of a good scientist is that he is never afraid to be wrong. He once remarked:

Science is no fun, if you are never wrong!

In choosing a hypothesis there is no virtue in timidity and no shame in sometimes being wrong.

The second quote is not supposed to be humorous by the way.

On most occasions however, Thomas Gold had this knack of turning out to be right inspite of facing intense criticism initially. Some of his heretical ideas that turned out right were:

1. Pitch Discriminative Ability of the Ear: One of the first of Tommy Gold’s ideas that was received with much hostility and was summarily rejected by the experts of the time was his theory and experiments on hearing and pitch discrimination. In 1946 immediately after the great war, Gold got interested in the ability of the human ear to discriminate the pitch of musical sounds. It was a question that was perplexing the auditory physiologists of the time, and Gold fresh from working with the royal navy on radars and communications thought of the physiology of hearing in those terms. The human ear can tell the difference when a pure tone changes by as little as one percent. Gold thought that the ear contained a set of resonators finely tuned, whereas the prevailing view of the time was that the internal structure of the ear was too weak and flabby to resonate and all the interpretation of the sounds and tones happened in the brain, with the information being communicated by neural signals.

Gold designed a very simple and elegant experiment to prove the experts, the professional auditory physiologists wrong. The experiment has been described by Freeman Dyson in his book, The Scientist as Rebel as he himself was a part of the experiment. Prof Freeman writes:

He (Gold) fed into the headphones a signal consisting of short pulses of a pure tone, separated by intervals of silence. The silent intervals were atleast ten times as long as the period of the pure tone. The pulses were all of the same shape, but they had phases that could be reversed independently….Sometimes Gold gave all the pulses the same phase and some times he alternated the phases so that the even pulses had one phase and the odd pulses had the opposite phase. All I had to do was to sit with the headphones on my ears and listen while Gold put in the signals with either constant or alternating phases. I had to tell him from the sound whether the phase was constant or alternating. When the silent intervals between pulses was ten times the period of the pure tone, it was easy to tell the difference. I heard a noise like a mosquito, a hum and a buzz sounding together, and the quality of the hum changed noticeably when the phases were changed from constant to alternating. We repeated the trials with longer silent intervals. I could still tell the difference, when the silent interval was as long as thiry periods.

This elegant experiment showed that the human ear could remember the phase of a signal after it has stopped for thirty times the period of the signal and proved that pitch discrimination was done not in the brain but in the ear. To be able to remember the phase, the ear should have finely tuned resonators that continue to vibrate during the period of silence.

Now armed with experimental evidence for his theory that pitch discrimination was done in the ear, Gold also had a theory on how there could be very finely tuned resonators made up of the weak and flabby material in the ear. He proposed that the ear involved an active – not a passive – receiver, one in which positive feedback, not just passive detection is involved. He said that the ear had an electrical feedback system, the mechanical resonators are coupled to the electrically powered sensors so that the overall system works like an active tuned amplifier. The positive feedback would counteract the dissipation taking place in the flabby internal structure of the ear.

Gold’s findings and ideas were rejected by the experts of the field, who said Gold was an ignorant outsider with absolutely no knowledge or training in physiology. Gold however always maintained he was right. Thirty years later, auditory physiologists armed with more sophisticated tools discovered that Gold was indeed correct. The electrical sensors and the feedback system in the ear were identified.

Gold’s two papers on hearing published in 1948 remain highly cited to this day.

2. Pulsars: One of his ideas that was rather quickly accepted was his idea on what a Pulsar was. After being discovered by radio astronomers Gold proposed that they were rotation neutron stars.

[A schematic of a Pulsar. Image Source: Wikipedia Commons]

After some initial disapproval this idea was accepted almost immediately by the “experts”. Gold himself has written this on this matter in an article authored by him titled The Inertia of Scientific Thought:

Shortly after the discovery of pulsars I wished to present an interpretation of what pulsars were, at this first pulsar conference: namely that they were rotating neutron stars. The chief organiser of this conference said to me, “Tommy, if I allow for that crazy an interpretation, there is no limit to what I would have to allow”. I was not allowed five minutes floor time, although I in fact spoke from the floor. A few months later, this same organiser started a paper with the sentence, “It is now generally considered that pulsars are rotating neutron stars”.

3. The Arrow of Time: In the 60s Gold wrote extensively on The Arrow of Time, and held the view that the universe will re collapse someday and that the arrow of time will reverse. His views remain controversial till today and a vast majority of cosmologists don’t even take it seriously. It remains to be seen if Gold’s hypothesis would be respected.

4. Polar Wandering: In the 1950s while at the royal observatory, Gold became interested in the instability of Earth’s axis of rotation or the wandering pole. He wrote a number of papers on plasmas and magentic fields in the solar system and also coined the term “The Earth’s Magnetosphere”. In 1955 he published yet another revolutionary paper “Instability of the Earth’s Axis of Rotation“. Gold made the view that large scale polar wandering could be expected to occur in relatively short geological time spans. That is, he expressed the possibility that the Earth’s axis of rotation could migrate by 90 degrees in a time of under a million years. This effectively means that in such a case, points at the equator would come to the poles and points at the poles would come at the equator. Gold argued that this 90 degree migration would be triggered by movements of mass that would cause the old axis of rotation to become unstable. A large accumulation of ice at the poles for example might be one reason why such a flip could occur. His paper was ignored largely for over 40-45 years, largely because at that time the research was focused on plate tectonics and continental drift.

In 1997 a Caltech professor Joseph Kirschvink, who is an expert in these areas published a paper that suggested that such a 90 degree flip indeed happened at least once in the past in the early Cambrian era. This holds much significance given the fact that this large scale migration of the poles coincides with the so called “Cambrian Explosion“. Gold’s work was finally confirmed after being ignored for decades.

5. Abiogenic Origin of Petroleum: When I first read about the theory of abiogenic origin of petroleum promoted by Tommy Gold and many Soviet and Ukrainian Geologists, I was immediately reminded of my old organic chemistry texts that spoke of the abiogenic origin theory given by Mendeleev almost 150 years ago. This was called Mendeleev’s Carbide Theory and it died after the biological theory of petroleum origin was widely accepted.

Speaking as a layman who has little knowledge of geology, petroleum etc, I would say any theory of petroleum origin must broadly explain the following points:

1. Its association with Brine.

2. Presence of $N$ and $S$ compounds.

3. Presence of biomarkers, chlorophyll and haemin in it.

4. It’s optically active nature.

According to Mendeleev’s Carbide theory:

1. The molten metals in the Earth’s interior combined with carbon from coal deposits to form the corresponding carbides.

• $Ca + 2C ---> Ca C_2$
• $Mg + 2C---> Mg C_2$
• $4Al + 3C---> Al_4 C_3$

2. The carbides reacted with steam or water under high temperature and pressure to form a mixture of saturated and unsaturated hydrocarbons.

• $Ca C_2 + 2H_2 O---> Ca(OH)_2 + C_@ H_2$
• $Al_4 C_3 +12H_2 O---> 4Al(OH)_3 +3C H_4$

3. The unsaturated hydrocarbons underwent a series of reactions such as hydrogenation, isomerisation, polymerisation and alkylation to form a number of hydrocarbons.

• $C_2 H_2 ---> C_2 H_4 ---> C_2 H_6$
• $3[C_2 H_2]---> C_6 H_6$

etc.

This theory got the support by the work of Moissan and Sabatier and Senderen. Moissan obtained a petroleum like liquid by the hydrogenation of Uranium Carbide, Sabatier and Senderen obtained a petroleum type substance by the hydrogenation of Acetylene.

However the theory was in time replaced by the theory of biological origin as it failed to account for:

1. The presence of Nitrogen and Sulphur compounds.

2. Presence of Haemin and Chlorophyll.

3. Optically active nature.

After almost hundred years, the abiogenic theory was resurrected by the great Russian geologist Nikolai Alexandrovitch Kudryavtse in 1951. This was worked on extensively by a number of Russians in the coming two decades.

In the west Thomas Gold was the only major proponent of it. And this is his most controversial theory, not only because it was opposed by powerful oil industry lobbyists but also because Gold faced much flak for plagiarism, something that Gold refused to acknowledge, in his later works he cited the works of the Russian scientists in the field. He maintained that he was simply not aware of the work done by the Soviet Geologists and that he cited their work once he became aware of it. Gold proposed that the natural gas and the oil came from reservoirs from deep within the Earth and are simply relics of the formation of the Earth. And that the biological molecules found in them did not show they had a biological origin but rather that they were contaminated by living creatures. He remained critical of the proponents of the theory of biological origin as then it could not be explained why there were hydrocarbon reserves on other planets when there had been no life on them. This theory remains controversial, Gold could not live to defend it. However an elegant experiment performed provides some evidence that Gold could indeed again be right.

Dyson wrote the following on an EDGE essay in this regard:

Just a few weeks before he died, some chemists at the Carnegie Institution in Washington did a beautiful experiment in a diamond anvil cell, [Scott et al., 2004]. They mixed together tiny quantities of three things that we know exist in the mantle of the earth, and observed them at the pressure and temperature appropriate to the mantle about two hundred kilometers down. The three things were calcium carbonate which is sedimentary rock, iron oxide which is a component of igneous rock, and water. These three things are certainly present when a slab of subducted ocean floor descends from a deep ocean trench into the mantle. The experiment showed that they react quickly to produce lots of methane, which is natural gas. Knowing the result of the experiment, we can be sure that big quantities of natural gas exist in the mantle two hundred kilometers down. We do not know how much of this natural gas pushes its way up through cracks and channels in the overlying rock to form the shallow reservoirs of natural gas that we are now burning. If the gas moves up rapidly enough, it will arrive intact in the cooler regions where the reservoirs are found. If it moves too slowly through the hot region, the methane may be reconverted to carbonate rock and water. The Carnegie Institute experiment shows that there is at least a possibility that Tommy Gold was right and the natural gas reservoirs are fed from deep below. The chemists sent an E-mail to Tommy Gold to tell him their result, and got back a message that he had died three days earlier.

6. The Deep Hot Biosphere: I am yet to read this book, though I have been thinking of reading it for almost a year now.

[The Deep Hot Biosphere, Image Source : Amazon]

In this controversial but famous theory Gold proposes that the entire crust of the Earth uptill a depth of a few miles is populated by living creatures. The biosphere that we see is only a very small part of it. The most ancient part of it is much larger and is much warmer. In 1992 Gold referred to ocean vents that pump bacteria from the depth of the Earth in support of his views. A number of such hydrothermal vents have since then been discovered. There is increasing evidence that his yet another controversial theory might just be right. Even if it is not, the evidence collected will help us understand our planet much better.

[A Black Smoker Hydrothermal Vent]

Finally Quoting Prof Freeman Dyson on him again:

Gold’s theories are always original, always important, usually controversial, and usually right.

1. The Scientist as Rebel : Chapter 3 – Freeman Dyson (Amazon)

2. The Inertia of Scientific Thought – Thomas Gold

3. The Deep Hot Biosphere – Thomas Gold

4. Heretical Thoughts about Science and Society – Freeman Dyson

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## Dr Radford Neal is now Blogging

I am absolutely delighted to have discovered that Prof Radford Neal is now blogging! And I am extremely pleased to post an announcement in this regard.

Prof Neal is a leading researcher in Statistical Computing, Pattern Recognition etc and is presently a Professor in the Department of Statistics and the Department of Computer Science at the University of Toronto. His home page can be accessed by clicking here. I hope his blog would help me (and us) in learning a lot more about statistics, especially for Machine Learning. For starters I would highly recommend his post on Down Syndrome and Decision Theory.

Quoting a rather nice paragraph from Dr Radford Neal’s PhD thesis. (Source):

Sometimes a simple model will outperform a more complex model . . . Nevertheless, I believe that deliberately limiting the complexity of the model is not fruitful when the problem is evidently complex. Instead, if a simple model is found that outperforms some particular complex model, the appropriate response is to define a different complex model that captures whatever aspect of the problem led to the simple model performing well.

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## Starting Afresh

Quoting the great English born American physicist, mathematician, writer, humanist Freeman Dyson ( Born December 15, 1923-).

[Photo Source: SNS-IAS, Princeton]

So long as you have courage and a sense of humor, it is never too late to start life afresh.

Very deep quote, especially if you think you can replace “life” with almost anything else. Probably we all know the fact so well put in this quote but refuse to acknowledge it when it matters.

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## The Best Machine Learning Course on the Web

Edit (November 05, 2011): Note that this post was made over THREE years ago. That time this was the only comprehensive Machine Learning course available online. Since then situation has changed. Professor Andrew Ng’s course has been offered online for everyone. Many other courses have also become available. Find some of these at the bottom of this post.

Just two weeks ago I posted a few lectures on Machine Learning, Learning Theory, Kernel Methods etc on this post. Since then my friend and guide Sumedh Kulkarni informed me of a new course on the Stanford University youtube channel on Machine Learning I have also indexed this channel on my post on Video Lectures.

Since then I have already seen half of it, and though it covers a very broad range, and is meant to be a first course on Machine Learning, it is in my opinion the best course on the web on the same. Most others I find boring because of either poor English of the instructor or bad recording or both.

The course is taken by Dr Andrew Ng, who has very good experience in teaching this course and working in Robotics, AI and Machine Learning in general. Incidentally he has been the guide of a PhD candidate Ashutosh Saxena, whose research papers we have used for a previous project on pattern recognition.

Dr Ng’s deep knowledge in the field can be felt in just some minutes into the first course which he makes even more interesting by his good communication skills and ability to make lectures more exciting and intuitive by adding fun videos in between.

The course details are as follows.

Course: Machine Learning (CS 229). It can be accessed over here: Stanford Machine Learning.

Instructor: Dr Andrew Ng.

Course Overview:

Lecture 1: Overview of the broad field of Machine Learning.

Lecture 2: Linear regression, Gradient descent, and normal equations and discussion on how they relate to machine learning.

Lecture 3: Locally weighted regression, Probabilistic interpretation and Logistic regression.

Lecture 4: Newton’s method, exponential families, and generalized linear models.

Lecture 5: Generative learning algorithms and Gaussian discriminative analysis.

Lecture 6: Applications of naive Bayes, neural networks, and support vector machine.

Lecture 7: Optimal margin classifiers, KKT conditions, and SUM duals.

Lecture 8: Support vector machines, including soft margin optimization and kernels.

Lecture 9: Learning theory, covering bias, variance, empirical risk minimization, union bound and Hoeffding’s inequalities.

Lecture 10: VC dimension and model selection.

Lecture 11: Bayesian statistics, regularization, digression-online learning, and the applications of machine learning algorithms.

Lecture 12: Unsupervised learning in the context of clustering, Jensen’s inequality, mixture of Gaussians, and expectation-maximization.

Lecture 13: Expectation-maximization in the context of the mixture of Gaussian and naive Bayes models, as well as factor analysis and digression.

Lecture 14: Factor analysis and expectation-maximization steps, and continues on to discuss principal component analysis (PCA).

Lecture 15: Principal component analysis (PCA) and independent component analysis (ICA) in relation to unsupervised machine learning.

Lecture 16: Reinforcement learning, focusing particularly on MDPs, value functions, and policy and value iteration.

Lecture 17: Reinforcement learning, focusing particularly on continuous state MDPs, discretization, and policy and value iterations.

Lecture 18: State action rewards, linear dynamical systems in the context of linear quadratic regulation, models, and the Riccati equation, and finite horizon MDPs.

Lecture 19: Debugging process, linear quadratic regulation, Kalmer filters, and linear quadratic Gaussian in the context of reinforcement learning.

Lecture 20: POMDPs, policy search, and Pegasus in the context of reinforcement learning.

Course Notes: CS 229 Machine Learning.

My gratitude to Stanford and Prof Andrew Ng for providing this wonderful course to the general public.

Other Machine Learning Video Courses:

1. Tom Mitchell’s Machine Learning Course.

Related Posts:

1. Demystifying Support Vector Machines for Beginners. (Papers, Tutorials on Learning Theory, Machine Learing)

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## Dating at Stanford

I originally intended to complete my post related to Game Theory + Swarm Intelligence. However, I see that I am not really in the mood for Maths just now.

I’d rather put up a PHD comics strip that cracks me up whenever I come across it. I happened to come across it in the morning and I decided to put it up. ;)

Originally published 2/2/1998, the copyright rests with the rightful owners and publisher.

Click to Enlarge

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