Posts filled under #learning

Multifunctional Hanging S

Multifunctional Hanging Soft Rattle for Baby $ 13.99 and FREE Worldwide Shipping Tag and Share with a Friend! Visit our store now and see our 300+ product catalog. Your kids will thank you! Free Shipping Worldwide! Toys, materials and costumes with a learning purpose. #kids #learning #toys #montessori #learning #lego #kidsscience #kidsmath #kidscreativity #creativity #buildingtoys #children #earlyeducation #diy #imaginaryplay #imaginary #kidscostumes #arts #crafts #artsandcrafts #alphabet #toddlers #infants #doityourself #musicaltoys #legos

@kpssnotlarim05
@sercan_h

@kpssnotlarim05 @sercan_hocaa @cografyasorudiyari @yds_yokdil_2017 @englishiseasyyy @englishwordtime @kpsssorudiyarii @onlineingilizceogren @almanca_shop @kpsskariyer.soru @aras_hoca @kpssce_cografya @gercekingilizce @widenyourword @tarihsorudiyari @kpssem.benim @yds_yokdil_2017 @yds_yokdil_lys5 @ingelistir @onlineingilizceogren @eglenceli_ingilizce @lys.5_yds_dilci @widenyourword @ingilizce_yi_yasamak @divanitarih.bilgi @3kelimeingilizce #yds #ykdil #lys5 #ales #kpss #learningenglish #learning #english

Day 15. #gomukhasana B fo

Day 15. #gomukhasana B for the #yogachallenge today with hosts: @ericarinyoga @gesticulate @greenideas80 @caribouyoga @cat_shanti @vesna108 #flexisummertribe ....love this double #bind for some #shoulder and #hip love . On a day that needs some serious #insights sometimes #binding and #learning to #unbind can perhaps shed some #light and #insight ... at least that's my #prayer for this day.. . . . #yogaeveryday #yogachallenges #nofear #lightandlove #yogamovement #changement #asana #balance #yoginilife #alwaysonthemove #yogaworld #onajourney #augustyogachallenge #yogafit #yogaoflife #yogaontherocks

8/27 Pre-Sale. Bundle. Ye

8/27 Pre-Sale. Bundle. Yes on TIDE Lots of freebies Super Hot Week If I receive any extra inserts, I will include them at no extra charge Coupons included $2/1 Tide $2/1 Tide pods Bogo Pantene Bogo Febreeze Oxi Head & Shoulders Suave All - Snuggles Degree Herbal Essence L'Oral Garner And many more I ONLY ship to the address linked to your PayPal account Please send pp as Goods and Services by clicking the link in my bio v_mazas454@yahoo.com Please Include your name, IG name, what you are ordering and address in the notes section I ship from Southern California. Items will start shipping Monday (possibly sooner) Please No e-Checks .#562couponers #coupons #couponcommunity #couponfairy #ilovecoupons #socalcouponer #eastcoastcouponer #westcoastcouponer #neverpayretail #earlyinserts #floridacouponers #newyorkcouponers #midwestcouponers #alabamacouponers #houstoncouponers #323couponers #couponcommunity #socalcouponer #learntocoupon #couponnewbies #socalcouponer #westcoastcouponer #310couponers #northerncalicouponers #209couponers #coupon101 #iso#washingtoncouponers #eastcoastcouponer #uft #californiainserts #couponfairy #alabamacouponers #couponinserts #floridacouponers #learning #newyorkcouponers

Sometimes in life things

Sometimes in life things come at you when you aren't ready, including love. The lovers card depicts a higher power watching over a pair of individuals; this card is often viewed as a lovey-dovey card, but I think we all know that sometimes your heart can lead you places you weren't expecting and it can tip everything upside down. Imagine Cupid strikes you and suddenly you are emotionally tied to someone (or something!) you weren't anticipating... something that may be affecting your ability to be the free-loving and commitment free creature you want to be. It's important to always remember to keep the balance, and tap into that strength you have inside you. Life is full of surprises but you are adaptable and strong! #tarotreading #tarot #tarotcard #tarotcards #indietarot #indiedeck #tarotcommunity #tarotdeck #thefoxtarot #crystals #lovers #sagittarius #strength #divination #tarotreader #tarotreadersofig #tarotreadersofinstagram #mystic #magic #learning #growing #blackandwhite #graphic #design #fortune

Imagine, if you will, thi

Imagine, if you will, this magnificent entity we call the sun one day received word that we humans admire the moon at night which goes through different phases a total of 13 times per real year. After receiving these words, the sun begins to envy the moon. One day, the sun decides to not show up for its daily labor of love. Instead, to everyone's surprise, it shows up in the middle of the night and tells the moon it wants to take its place. The moon explains to the sun the inherent value the sun possesses and that it must continue its daily inspirational discipline for the sake of the all. The sun insists that it wants to be like the moon and it wants to take its place. The moon again begs the sun to go back to its post and continue on its special journey. Luckily for all of us, the powerful sun remembered its journey, its abilities as a sun, and its special purpose and decided to return to its duty and develop all of its capabilities. Happily ever after... #randomthoughts _____________________________________________ #awaken #awakening #blackhistory #education #fitness #goals #healing #history #internalreparations #knowledge #lawoftime #learning #love #maat #marathon #mind #mindfulness #psychology #rebuild #recovery #reparations #respect #selfcontrol #soul #student #think #truth #universe

Aram has many fears to ev

Aram has many fears to everything unknow for him and is advancing step by step. These days he's discovering the noises of the shower and is not clear enough... . Aram tiene muchos miedos que vamos trabajando poco a poco. Estos das le toca el turno a los ruidos de la ducha... Y no lo tiene nada claro... . #Aram #shower #noises #discovering #fears #sorolls #ducha #undiaqualsevol #normalday #adaptacion #ruidos #stepbystep #adopted #rescuedog #newlife #mixdog #mestizo #adoptado #adoptanocompres #adoptdontshop #miedos #learning #aprendiendo

An extract on #learning

Machine learning is closely related to (and often overlaps with) computational statistics, which also focuses on prediction-making through the use of computers. It has strong ties to mathematical optimization, which delivers methods, theory and application domains to the field. Machine learning is sometimes conflated with data mining, where the latter subfield focuses more on exploratory data analysis and is known as unsupervised learning. Machine learning can also be unsupervised and be used to learn and establish baseline behavioral profiles for various entities and then used to find meaningful anomalies. Within the field of data analytics, machine learning is a method used to devise complex models and algorithms that lend themselves to prediction; in commercial use, this is known as predictive analytics. These analytical models allow researchers, data scientists, engineers, and analysts to "produce reliable, repeatable decisions and results" and uncover "hidden insights" through learning from historical relationships and trends in the data. As of 2016, machine learning is a buzzword, and according to the Gartner hype cycle of 2016, at its peak of inflated expectations. Effective machine learning is difficult because finding patterns is hard and often not enough training data is available; as a result, machine-learning programs often fail to deliver.

Tom M. Mitchell provided a widely quoted, more formal definition of the algorithms studied in the Machine Learning field: "A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E." This definition of the tasks in which machine learning is concerned offers a fundamentally operational definition rather than defining the field in cognitive terms. This follows Alan Turing's proposal in his paper "Computing Machinery and Intelligence", in which the question "Can machines think?" is replaced with the question "Can machines do what we (as thinking entities) can do?". In Turing's proposal the various characteristics that could be possessed by a thinking machine and the various implications in constructing one are exposed.

Machine learning tasks are typically classified into three broad categories, depending on the nature of the learning "signal" or "feedback" available to a learning system. These are Supervised learning: The computer is presented with example inputs and their desired outputs, given by a "teacher", and the goal is to learn a general rule that maps inputs to outputs. Unsupervised learning: No labels are given to the learning algorithm, leaving it on its own to find structure in its input. Unsupervised learning can be a goal in itself (discovering hidden patterns in data) or a means towards an end (feature learning). Reinforcement learning: A computer program interacts with a dynamic environment in which it must perform a certain goal (such as driving a vehicle or playing a game against an opponent). The program is provided feedback in terms of rewards and punishments as it navigates its problem space. Between supervised and unsupervised learning is semi-supervised learning, where the teacher gives an incomplete training signal: a training set with some (often many) of the target outputs missing. Transduction is a special case of this principle where the entire set of problem instances is known at learning time, except that part of the targets are missing. Among other categories of machine learning problems, learning to learn learns its own inductive bias based on previous experience. Developmental learning, elaborated for robot learning, generates its own sequences (also called curriculum) of learning situations to cumulatively acquire repertoires of novel skills through autonomous self-exploration and social interaction with human teachers and using guidance mechanisms such as active learning, maturation, motor synergies, and imitation. Tasks can be categorized into deep learning (the application of artificial neural networks to learning tasks that contain more than one hidden layer) and shallow learning (tasks with a single hidden layer). Another categorization of machine learning tasks arises when one considers the desired output of a machine-learned system: In classification, inputs are divided into two or more classes, and the learner must produce a model that assigns unseen inputs to one or more (multi-label classification) of these classes. This is typically tackled in a supervised way. Spam filtering is an example of classification, where the inputs are email (or other) messages and the classes are "spam" and "not spam". In regression, also a supervised problem, the outputs are continuous rather than discrete. In clustering, a set of inputs is to be divided into groups. Unlike in classification, the groups are not known beforehand, making this typically an unsupervised task. Density estimation finds the distribution of inputs in some space. Dimensionality reduction simplifies inputs by mapping them into a lower-dimensional space. Topic modeling is a related problem, where a program is given a list of human language documents and is tasked to find out which documents cover similar topics.

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