LetterTo MyFather
JF-Expert Member
- Jan 8, 2014
- 308
- 668
Thread Closed!!
Thread Closed!!Tatizo lako ni uwezo mdogo wa kufikiri au kutokujua google inavyofanya kazi. Ni dhahiri huelewi hata "latent semantic indexing" ni nini. Kiufupi ni teknolojia inayotumiwa na google algorithms kutoa relevant search engine result pages (SERP ).
"Neural network analysis" ambayo imekuwa ni core architecture ya google algorithms kwa miaka ya hivi karibuni ikiwa ni tofauti na ile ya zamani iliyoitwa "Pagerank" au "link analysis" imekuwa ina favors results kutokana na kitu kinaitwa "social response" na geo targeting (geographic position).
Social response based algorithms zinaangalia zaidi "user generated content sites" kama Facebook, JF, Youtube, Instagram n.k kuona nani yuko wapi na anaongea nini.
Kwa lugha rahisi google hutoa SERP kutokana na mahali ulipo, sasa wewe umeona hiyo 67.9% poverty rate ukakurupuka na kuja kuanzisha mada. Usichokijua ni kuwa google imekupa hiyo SERP kwa kuwa imebaini (baada ya kufanya Neural network analysis) kuwa wakenya wanafurahia kuisema vibaya Tanzania na results hizi zitakuwa more favorable kwa mtu aliye Kenya. Kwa ushamba wako ukadhani kila mtu duniani aki google "tanzania poverty rate" atapata results kama zako.
Keyword hiyo hiyo, niki search hapa Marekani napata results tofauti kabisa kwa kuwa google inajua watu wa hapa hawana shida na Tanzania na results za google zinakuwa unbiased.
Utaona kwenye results zangu hapo chini inaonesha tofauti na yako, umasikini ukiwa 49.1% kwa mwaka 2011 kutoka 55.1% mwaka 2007 kwa trend hiyo inamaanisha kwa mwaka huu, 2019 umasikini utakuwa umepungua zaidi kama page ya worldbank inavyothibitisha hapo chini.
View attachment 1098107
haujielewi dogo... jaribu kumakinika kiasi.Kama Kenya wanajiita middle income lakini wananchi wao ni masikini wa kutupwa
Sawa mama watotohaujielewi dogo... jaribu kumakinika kiasi.
usitie shaka mremboSawa daddy
49% living in extreme poverty.Endelea kujipa moyo, Wakati masikini tz anajimudu na anakula vizuri na anaishi vizuri tofauti na huko kwenu masikini ni masikini kweli kweli hadi huruma
49% living in extreme poverty.View attachment 1098826
49%Achana na mitandao tembelea ndo utaona
Shikamoo Mkuu,nimepata Elimu hapa,AsanteTatizo lako ni uwezo mdogo wa kufikiri au kutokujua google inavyofanya kazi. Ni dhahiri huelewi hata "latent semantic indexing" ni nini. Kiufupi ni teknolojia inayotumiwa na google algorithms kutoa relevant search engine result pages (SERP ).
"Neural network analysis" ambayo imekuwa ni core architecture ya google algorithms kwa miaka ya hivi karibuni ikiwa ni tofauti na ile ya zamani iliyoitwa "Pagerank" au "link analysis" imekuwa ina favors results kutokana na kitu kinaitwa "social response" na geo targeting (geographic position).
Social response based algorithms zinaangalia zaidi "user generated content sites" kama Facebook, JF, Youtube, Instagram n.k kuona nani yuko wapi na anaongea nini.
Kwa lugha rahisi google hutoa SERP kutokana na mahali ulipo, sasa wewe umeona hiyo 67.9% poverty rate ukakurupuka na kuja kuanzisha mada. Usichokijua ni kuwa google imekupa hiyo SERP kwa kuwa imebaini (baada ya kufanya Neural network analysis) kuwa wakenya wanafurahia kuisema vibaya Tanzania na results hizi zitakuwa more favorable kwa mtu aliye Kenya. Kwa ushamba wako ukadhani kila mtu duniani aki google "tanzania poverty rate" atapata results kama zako.
Keyword hiyo hiyo, niki search hapa Marekani napata results tofauti kabisa kwa kuwa google inajua watu wa hapa hawana shida na Tanzania kwa hiyo results za google zinakuwa unbiased.
Utaona kwenye results zangu hapo chini inaonesha tofauti na zako, umasikini ukiwa 49.1% kwa mwaka 2011 kutoka 55.1% mwaka 2007. Kwa trend hiyo inamaanisha kwa mwaka huu, 2019 umasikini utakuwa umepungua zaidi kama page ya worldbank inavyothibitisha hapo chini.
View attachment 1098107
๐ ๐ f*ck sawa. Hard to counter that, so wacha nilaleTatizo lako ni uwezo mdogo wa kufikiri au kutokujua google inavyofanya kazi. Ni dhahiri huelewi hata "latent semantic indexing" ni nini. Kiufupi ni teknolojia inayotumiwa na google algorithms kutoa relevant search engine result pages (SERP ).
"Neural network analysis" ambayo imekuwa ni core architecture ya google algorithms kwa miaka ya hivi karibuni ikiwa ni tofauti na ile ya zamani iliyoitwa "Pagerank" au "link analysis" imekuwa ina favors results kutokana na kitu kinaitwa "social response" na geo targeting (geographic position).
Social response based algorithms zinaangalia zaidi "user generated content sites" kama Facebook, JF, Youtube, Instagram n.k kuona nani yuko wapi na anaongea nini.
Kwa lugha rahisi google hutoa SERP kutokana na mahali ulipo, sasa wewe umeona hiyo 67.9% poverty rate ukakurupuka na kuja kuanzisha mada. Usichokijua ni kuwa google imekupa hiyo SERP kwa kuwa imebaini (baada ya kufanya Neural network analysis) kuwa wakenya wanafurahia kuisema vibaya Tanzania na results hizi zitakuwa more favorable kwa mtu aliye Kenya. Kwa ushamba wako ukadhani kila mtu duniani aki google "tanzania poverty rate" atapata results kama zako.
Keyword hiyo hiyo, niki search hapa Marekani napata results tofauti kabisa kwa kuwa google inajua watu wa hapa hawana shida na Tanzania kwa hiyo results za google zinakuwa unbiased.
Utaona kwenye results zangu hapo chini inaonesha tofauti na zako, umasikini ukiwa 49.1% kwa mwaka 2011 kutoka 55.1% mwaka 2007. Kwa trend hiyo inamaanisha kwa mwaka huu, 2019 umasikini utakuwa umepungua zaidi kama page ya worldbank inavyothibitisha hapo chini.
View attachment 1098107
Okay first you are wrong i get the same result as you when searching from kenya, PageRank does solely depend on location, it depends on the number and quality of links to a particular page using factors such as the words of your query, relevance and usability of pages, expertise of sources which are all weighted i.e location carries less weight than expert sources , it constantly updates itself so item one today may be item three the next day or the next month.Tatizo lako ni uwezo mdogo wa kufikiri au kutokujua google inavyofanya kazi. Ni dhahiri huelewi hata "latent semantic indexing" ni nini. Kiufupi ni teknolojia inayotumiwa na google algorithms kutoa relevant search engine result pages (SERP ).
"Neural network analysis" ambayo imekuwa ni core architecture ya google algorithms kwa miaka ya hivi karibuni ikiwa ni tofauti na ile ya zamani iliyoitwa "Pagerank" au "link analysis" imekuwa ina favors results kutokana na kitu kinaitwa "social response" na geo targeting (geographic position).
Social response based algorithms zinaangalia zaidi "user generated content sites" kama Facebook, JF, Youtube, Instagram n.k kuona nani yuko wapi na anaongea nini.
Kwa lugha rahisi google hutoa SERP kutokana na mahali ulipo, sasa wewe umeona hiyo 67.9% poverty rate ukakurupuka na kuja kuanzisha mada. Usichokijua ni kuwa google imekupa hiyo SERP kwa kuwa imebaini (baada ya kufanya Neural network analysis) kuwa wakenya wanafurahia kuisema vibaya Tanzania na results hizi zitakuwa more favorable kwa mtu aliye Kenya. Kwa ushamba wako ukadhani kila mtu duniani aki google "tanzania poverty rate" atapata results kama zako.
Keyword hiyo hiyo, niki search hapa Marekani napata results tofauti kabisa kwa kuwa google inajua watu wa hapa hawana shida na Tanzania kwa hiyo results za google zinakuwa unbiased.
Utaona kwenye results zangu hapo chini inaonesha tofauti na zako, umasikini ukiwa 49.1% kwa mwaka 2011 kutoka 55.1% mwaka 2007. Kwa trend hiyo inamaanisha kwa mwaka huu, 2019 umasikini utakuwa umepungua zaidi kama page ya worldbank inavyothibitisha hapo chini.
View attachment 1098107
It's funny you saying Neural network analysis has nothing to do with computing, so you want me to throw in terms like turing computability, recursive function, artificial neural network and deep learning just to show that I know something about computing? For what! That's not how I roll.Okay first you are wrong i get the same result as you when searching from kenya, PageRank does solely depend on location, it depends on the number and quality of links to a particular page using factors such as the words of your query, relevance and usability of pages, expertise of sources which are all weighted i.e location carries less weight than expert sources , it constantly updates itself so item one today may be item three the next day or the next month.
Also in computing there is nothing called "Neural network analysis" this is marketing term for those who do not understand artificial intelligence, what happens is a deep learning engine goes through the information produces a hypothesis this hypothesis is supervised by page rank ie. A neural network is unsupervised learning while page rank is supervised. In computing we use the supervised algorithms to check the result of the unsupervised algorithms.
Of course there are other neural networks that can self supervise but google does not use those in search instead they use them to optimize their data centres look at deep mind and recurrent neural network.
Page rank is still the backbone of google search engine combined with natural language processing and other smaller supervised algorithms. He is not wrong it is that just at the time he was searching that was the page that had the most relevant rank.
Kua muafrika ni mtihani kweli kweli
Google ni search engine tu,sema hizo websites!Lakini Google si watu wazuri
"Neural network analysis " Who said it has nothing to do with computing, i stated it is a marketing term not a computing term. The correct term "Neural network learning". Here is a link from google itself showing you how they do search and page rank is pretty much the backbone of their search. I am telling you not as a third party integrator but as a former google kenya employee and developer evangelist for microsoft kenya, who now runs a data company utilizing AI (Deep learning) to learn consumer behavior patterns in kenya.It's funny you saying Neural network analysis has nothing to do with computing, so you want me to throw in terms like turing computability, recursive function, artificial neural network and deep learning to show that I know something about computing? For what! That's not how I row.
Just so you know, you 're arguing with someone who spent quite sometime in the wild and created systems of crawlers and numerous algos to study google's indexing for the past 18 years and have seen how google has evolved over time.
What you stated about Page Rank (PR) is obsolete idea . PR was google's brain child in the 90's as it originated from Larry's backrub paper he published while still a graduate student at Stanford. When google was first launched, page rank was their core architecture.
Over the years they stopped using it (pageRank) because people started abusing Google results by creating multiple pages to link to a particular site to fool google about it's importance. I have thousands upon thousands of google indices stored on my harddrives (for the past 18 years) and I can tell you for fact that google doesn't put much weight on PR anymore.
The other thing that you're not aware about Google (in recent years) is that they're money hungry. After they went public in 2005, they are not so much into relevancy game as they did in the past. Now all they do is following the money, and that's where you come in with artificial deep learning. Investors have been pressuring them to reach their quarters, so they design systems to sniff where dollars are even at the expense of giving garbage results.
Hehehe Amerture diploma IT holderOkay first you are wrong i get the same result as you when searching from kenya, PageRank does solely depend on location, it depends on the number and quality of links to a particular page using factors such as the words of your query, relevance and usability of pages, expertise of sources which are all weighted i.e location carries less weight than expert sources , it constantly updates itself so item one today may be item three the next day or the next month.
Also in computing there is nothing called "Neural network analysis" this is marketing term for those who do not understand artificial intelligence, what happens is a deep learning engine goes through the information produces a hypothesis this hypothesis is supervised by page rank ie. A neural network is unsupervised learning while page rank is supervised. In computing we use the supervised algorithms to check the result of the unsupervised algorithms.
Of course there are other neural networks that can self supervise but google does not use those in search instead they use them to optimize their data centres look at deep mind and recurrent neural network.
Page rank is still the backbone of google search engine combined with natural language processing and other smaller supervised algorithms. He is not wrong it is that just at the time he was searching that was the page that had the most relevant rank.
Wuueh..Hapa siwesi comment! Ni kama kujaribu kushindana na ndovu kunyaIt's funny you saying Neural network analysis has nothing to do with computing, so you want me to throw in terms like turing computability, recursive function, artificial neural network and deep learning just to show that I know something about computing? For what! That's not how I row.
Just so you know, you're arguing with someone who spent quite sometime in the wild and created systems of crawlers and numerous algos to study google's indexing for the past 18 years and have seen how google has evolved over time.
What you stated about Google using Page Rank (PR) is an obsolete idea. PR was google's brain child in the 90's as it originated from Larry's backrub paper he published while still a graduate student at Stanford. When google was first launched, page rank was their core architecture.
Over the years they stopped using it (pageRank) because people started abusing Google results by creating multiple pages to link to a particular site to fool google about it's importance. I have thousands upon thousands of google indices stored on my harddrives (for the past 18 years) and I can tell you for fact that google doesn't put much weight on PR anymore.
The other thing that you're not aware about Google (in recent years) is that they're money hungry. After they went public in 2005, they are not so much into relevancy game as they did in the past. Now all they do is following the money, and that's where you come in with artificial deep learning. Investors have been pressuring them to reach their quarters, so they design systems to sniff where dollars are even at the expense of giving garbage results.
You're admitting to not knowing much about search."Neural network analysis " Who said it has nothing to do with computing, i stated it is a marketing term not a computing term. The correct term "Neural network learning". Here is a link from google itself showing you how they do search and page rank is pretty much the backbone of their search. I am telling you not as a third party integrator but as a former google kenya employee and developer evangelist for microsoft kenya, who now runs a data company utilizing AI (Deep learning) to learn consumer behavior patterns in kenya.
I have also worked for several european companies and american companies. I have 12 years of experience in this field called "software development" with international experience including danish police.
I know you did search engine optimization (seo) that is beginner knowledge and does not give you the inner workings of google.
I have had the pleasure of working with deep mind and google brain but they do not use them for search instead they use them for research into self driving cars, data centre optimization and health information analysis where deepmind is used in the UK NHs.
You really think google will tell the truth about their business secrets on the website? Your naivety is beyond measure.How Does Google Determine Ranking Results - Google Search
Discover how key factors such as meaning, relevance, and quality are used to generate how websites are ranking on Google.www.google.com
Mkuu ChamotoIt's funny you saying Neural network analysis has nothing to do with computing, so you want me to throw in terms like turing computability, recursive function, artificial neural network and deep learning just to show that I know something about computing? For what! That's not how I row.
Just so you know, you're arguing with someone who spent quite sometime in the wild and created systems of crawlers and numerous algos to study google's indexing for the past 18 years and have seen how google has evolved over time.
What you stated about Google using Page Rank (PR) is an obsolete idea. PR was google's brain child in the 90's as it originated from Larry's backrub paper he published while still a graduate student at Stanford. When google was first launched, page rank was their core architecture.
Over the years they stopped using it (pageRank) because people started abusing Google results by creating multiple pages to link to a particular site to fool google about it's importance. I have thousands upon thousands of google indices stored on my harddrives (for the past 18 years) and I can tell you for fact that google doesn't put much weight on PR anymore.
The other thing that you're not aware about Google (in recent years) is that they're money hungry. After they went public in 2005, they are not so much into relevancy game as they did in the past. Now all they do is following the money, and that's where you come in with artificial deep learning. Investors have been pressuring them to reach their quarters, so they design systems to sniff where dollars are even at the expense of giving garbage results.
It's social engineering, some people have tricked google into believing that the word idiot and Trump are synonymous.Mkuu Chamoto
When you google "idiot" in any locationView attachment 1099283 Picture of Trump is Ranked first. What would be the logic behind this?