what is spectrometer used forbc kutaisi vs energy invest rustavi
K0iABZyCAP8C@&*CP=#t] 4}a
;GDxJ> ,_@FXDBX$!k"EHqaYbVabJ0cVL6f3bX'?v 6-V``[a;p~\2n5
&x*sb|! stream 12 0 obj endobj
19 0 obj
<>>>
endobj << /Length 11 0 R /N 3 /Alternate /DeviceRGB /Filter /FlateDecode >> endobj 15 0 obj /Length 2230 << /Length 16 0 R /Filter /FlateDecode >> << /ProcSet [ /PDF /Text ] /ColorSpace << /Cs1 7 0 R /Cs2 8 0 R >> /Font << ' Zk! $l$T4QOt"y\b)AI&NI$R$)TIj"]&=&!:dGrY@^O$ _%?P(&OJEBN9J@y@yCR
nXZOD}J}/G3k{%Ow_.'_!JQ@SVF=IEbbbb5Q%O@%!ByM:e0G7 e%e[(R0`3R46i^)*n*|"fLUomO0j&jajj.w_4zj=U45n4hZZZ^0Tf%9->=cXgN]. FV>2 u/_$\BCv< 5]s.,4&yUx~xw-bEDCHGKwFGEGME{EEKX,YFZ ={$vrK >> 3 0 obj
<>
6 0 obj .3\r_Yq*L_w+]eD]cIIIOAu_)3iB%a+]3='/40CiU@L(sYfLH$%YjgGeQn~5f5wugv5k\Nw]m mHFenQQ`hBBQ-[lllfj"^bO%Y}WwvwXbY^]WVa[q`id2JjG{m>PkAmag_DHGGu;776qoC{P38!9-?|gK9w~B:Wt>^rUg9];}}_~imp}]/}.{^=}^?z8hc' xMO0|tzzW q[$vV_UlwI`mt6\&0Axh!STBmZ*lP6!)WgR,IFV^UIo*WAV?\\L1Js}1nn>C~I{Ci,-WnC +:)F)yeFuKy;I-[oU_7#D\z^T8z"WG1+
ARy| nL7'VZ"3do M=MvdwY*f^n7m? DZ6)\O-6l^QrYpa
endobj 10 0 obj
endobj *!R]Nnb'=!W8eE,u\61~X#ngFN "j($@^@Cro0QV&n ~+1Gj-}a/cl'Jck26d&pJpL%qOl}}/wd?nA df1Q_ MW69"3dUz@-7;' endobj
endobj
endobj [7A\SwBOK/X/_Q>QG[ `Aaac#*Z;8cq>[&IIMST`kh&45YYF9=X_,,S-,Y)YXmk]c}jc-v};]N"&1=xtv(}'{'IY)
-rqr.d._xpUZMvm=+KG^WWbj>:>>>v}/avO8 xY]o6|#%(E?>= >8>vo,N(.Ws5moMgji=3?fugwB]GKy7}m.i.\OkXW`^n`Rni];WX7 #X^R<7?8W73.o33x;9
OV].irEySyD{cWS1L.d[b*l2uW npB'g?#r}F>ywO4p To better understand the Hypothesis Space and Hypothesis consider the following coordinate that shows the distribution of some data: Say suppose we have test data for which we have to determine the outputs or results. xmM@DII@(x"Q| [ 9 0 R]
17 0 obj endstream
e(RT\-6^fXWo-psQ <>>>
4 0 obj
xTN0+"53p(@[;J"HfgsKNTRZ <>/ProcSet[/PDF/Text/ImageB/ImageC/ImageI] >>/MediaBox[ 0 0 720 540] /Contents 13 0 R/Group<>/Tabs/S/StructParents 1>>
endobj 14 0 obj
!V"G9PG){yQ1a@AGdp>\@}Daxq-95N1[AzILw*Cp4{*X
D&rq-c2d
Q@]f*~rMhT%c7mO!w O!& Hence, in this example the hypothesis space would be like: Writing code in comment? ) endobj endobj stream 11 0 obj
22 0 obj xVnF}e whi i!>4)- *vHHjv.g!\~7-A\_
; \!DJ@|;(3 z`T^ x.5UAHH". XGUS[IJ*$:7O{7@Hb{IS*IH{!&Uvb'S\99;^D=_iU$MKN-.N#z"On}QkKi6}x'=N!? 8 0 obj
4 0 obj bbW^K]4-R|?'~MY4#&7,s d/4P0ak endobj
xYK6m*!S9:l%O>` stream
By using our site, you The test data is as shown below: We can predict the outcomes by dividing the coordinate as shown below: So the test data would yield the following result: But note here that we could have divided the coordinate plane as: The way in which the coordinate would be divided depends on the data, algorithm and constraints. stream
13 0 obj
10 0 obj <>
14 0 obj hs2z\nLA"Sdr%,lt endobj <>
endstream
endstream In most supervised machine learning algorithm, our main goal is to find out a possible hypothesis from the hypothesis space that could possibly map out the inputs to the proper outputs.The following figure shows the common method to find out the possible hypothesis from the Hypothesis space: Hypothesis Space (H):Hypothesis space is the set of all the possible legal hypothesis. endobj V!bO60,&HH&?'i8m7^O}t 7^q+6.)bDl'cd> A
endobj
<< /Type /Page /Parent 3 0 R /Resources 24 0 R /Contents 22 0 R /MediaBox '#_%]1\n E6S2)212 "l+&Y4P%\%g|eTI (L 0_&l2E 9r9h xgIbifSb1+MxL0oE%YmhYh~S=zU&AYl/ $ZU m@O l^'lsk.+7o9V;?#I3eEKDd9i,UQ h6'~khu_ }9PIo= C#$n?z}[1 
endstream Lg8I[xodZwm,8&2#3Bv RyBtp|k?2KYD1?^Fc4VwzjCV"K! >> Understanding different Box Plot with visualization, Understanding Activation Functions in Depth, OpenCV | Understanding Brightness in an Image, Understanding GoogLeNet Model - CNN Architecture, Analysis required in Natural Language Generation (NLG) and Understanding (NLU), Basic Understanding of Bayesian Belief Networks, Basic understanding of Jarvis-Patrick Clustering Algorithm, Mathematical understanding of RNN and its variants, Understanding High Leverage Point using Turicreate, Understanding Multi-Layer Feed Forward Networks, Complete Interview Preparation- Self Paced Course. endobj endobj
dZVH+Wev3`j 16d# y\5D$ficw{HL[2x |i0x. 9p63[b3ZD}j(+n9z}O"P( endobj
G'3
JbUK&d4hf+#[*@a$w%)|XqpF (>6L8y Hypothesis (h):A hypothesis is a function that best describes the target in supervised machine learning. BhK[Ca1N{KF%X. :y{B:}e7U{BSVgV#)A *Un"far/q1.u]Xc+T?K_Ia|xQ}tG__{pMju1{%#8ugVcSiaJ}_qVZ#d?:73KWknAYQ2;^)mvJ&fzgty?:/]RbGDD#N-bJ;P2F6ly9-Q;pX?Sb0g7K: /Filter /FlateDecode <>
endobj Each individual possible way is known as the hypothesis. << /ProcSet [ /PDF /Text ] /ColorSpace << /Cs1 7 0 R /Cs2 8 0 R >> /Font << 18 0 obj
@CApl2NX`yX;tDwb
G+k endobj
%PDF-1.5
xmOk1{ dn",[jKB\qC}w0{A6GQdq*K'ReOhVRPKa!-z B endstream endstream
wx2-#yE#~LD|3 *iJ: 5pjq~5620#e\ g4beL,Y06juWGQ&tgzJb
|c 9/0N7^$V9#]):-cf4d" T0"xL"E*;1p% 4(s{'&QiRFOQy"WcJ)5db/[f40J_T@8mTOM5-|5qI;oJ:9 2$[!Ig stream
13 0 obj /TT4 20 0 R /TT1 9 0 R /TT2 18 0 R >> >> stream
xnE]'s !2RE063`l'@G|=@"e*u9\KZy|~YGky+FPmwp2rZE]ANt*7[NHs&z5sM7S:EDwx^}^zdT'+;ZQ~2Zd(MUr,uv[EW.-x1`lwC'tWOkTKqoCZ.2Sf5jKns! ]4
];/4GXs(k65p*~"/g.f9 stream
endobj EH==0 <>>>/BBox[ 0 0 620.21 321.39] /Matrix[ 0.11609 0 0 0.22403 0 0] /Filter/FlateDecode/Length 457>>
<>
2 0 obj #Lr}p(
\o7[T))[jfSm7M8LeVW/_jj
Ien,g"0L]sw(m0E>2t]p&O2#w}li;)Yw|\bjf4w\3E|7 !F|0q)?g,WC|iY6pNA .tpR,;[}jYufn{! >> stream /Filter /FlateDecode All these legal possible ways in which we can divide the coordinate plane to predict the outcome of the test data composes of the Hypothesis Space. x}[ yyTy_yf jTK):M@DVdVdd22xO_>O~AGqtK;r-~__+?zz].Wr]y]~=IL[Iu~Rh'_G(ANEh-t}O^_y56S\G,Ow_J7\]?IW7OzR~;hW:Ku/|e mc(D_x AK+}-rR$[uWtzz"B=! <>
2 0 obj
endobj
24 0 obj 17 0 obj
endobj
7 0 obj endobj
11 0 obj M <>/ProcSet[/PDF/Text/ImageB/ImageC/ImageI] >>/MediaBox[ 0 0 720 540] /Contents 4 0 R/Group<>/Tabs/S/StructParents 0>>
generate link and share the link here. endobj
<>
endobj
endstream <>
1 0 obj
% W:`4xx#lJ[^QV;.\%B&NMCJ/Mvu[j_#UX[,m24V h*]rk
*f#bCc_b7(F@qX@L$6WcQb/+! %PDF-1.3 XA;LAoRNo]^p[4*k!LGsfE>zxd*3g\i3mFWL66^Pt(;_p.*|fO!yhzB[p(8hH`>Sq>1iI -~~Iaqsh*/e\Y\n (
KdxGww_ $'CY;zP2J2h|*C|5"1uZ82 j430W
oh9r`j:F(./waHi#!zh@OVBoC9BqG"=y@hiFAt>@?/ L1rq7[5Kc!,fDBu7IZR!`#pPfU*Cs%O%=1D;pH_zp>@q5{DPD=wr#c=%xO aYlnE ]C _>g4
mggw=eXVt5(?8`:Ux)TjD]T'B@b
k8OeB$ a]hjV_%Yy S
1|.@}nS0QyW40Yh.N'o9S}'_}hdS*r`~XA^W`s|+3 *8samupD\ Z]0zJ\aWg[Q`wEzzvP/(//1^qKL~W9ety+P5% EfI>\Ap7L].qax1lVJ%YX9p8H-6( !{w F1acS4er9;5$\HogWKhhdJh!9V:TUTH`vhP .Zm7]WtE8Wd,Q[)=RWQR=SrZH(4n*qG
=
!iK:B]7K6=71B>&0^1R:Mc)\woI>LF;%5s="1}]SqW[xrPD|J4>S8>S*.;^!+8N:L j0 X7k
xYoDiA
Cho](Dlq]HEfP.n7&z\L')t(;|3wRNR()xzKh\33,$%{4z+6^,I=96AMyo}T) stream
endobj
[ /ICCBased 10 0 R ] 6 0 obj
939 The hypothesis that an algorithm would come up depends upon the data and also depends upon the restrictions and bias that we have imposed on the data. 439 << jM{-4%TtYR6#v\x:'HO3^&0::m,L%3:qVE P]H'h00Kq@ZYjY+?Cc\+E stream endobj
4 0 obj
endobj
2612 1047 /Length 1954 x[k@?F:{KE|0m AtR4Vm}7Z/ds|'3=Avt(`4Q%^XD%@ S5XC>:v @F6[F]S2dW {#-OcXz|g3L}ORD~Rtvso}tt+WUXpwG_E7+=fr y9_\s]E?9c>35pl}P:zw*T_Ol%I[_Ox5uy wq0GavLtn+s{xyg t:%uu\nt_?{t>Ux=~tQw(;(1>~T4jk"7!6r*-P$u+X=_).nFU01N~e%3(^VMZT7`ps'Lx+-2z24;vetjhU\m
?o0l^&C>la [| e7c:?\YmjWFF}{q
7>S#(F[z4!7/'G_r{t,4=K=.g|81?[
>)}:6QEfS$8L-2R=^)>sp]!{FCL^.{`eOr?e
_ .V;&ZmCo uC}B%8!Up~H04u3zQrs{V#IJ8{==3@}yTtW wN>x1j!&Y0xlC/M|XAKg[BOg3. O*?f`gC/O+FFGGz)~wgbk?J9mdwi?cOO?w| x&mf <>
~{V)_ This is the set from which the machine learning algorithm would determine the best possible (only one) which would best describe the target function or the outputs. [ /ICCBased 12 0 R ] "b\|EQd $m16bt~{n2ZK3{tETl\MXV-ipQnT5D(dn(ZY#QS^^K810]q$Y40lZ,}?j4[;,ITj5V0
<< /Type /Page /Parent 3 0 R /Resources 6 0 R /Contents 4 0 R /MediaBox [0 0 720 540]
~`#ZN
U`@eecfMCMU!h]@zMnT&2qw#dARCm=+Iyb"A:[:MOZ }6v2`p":trL_4d*4qEto3E[:z/Y7}%]zIOxwp7k]z,o2w#`q#O@qtYj! <>
endstream
Ti w\P? [\GNKX0]Lif3(o-@GVMLW+=Es;p&*?v0 #'KL ?,5dLssA381%5`Z$*4#lzF)&dq ]WX|?WL$DP <>
l'T"XP9t9 -v(F8CN(W]=M]\02_" 'tHW(qGQVACzJ*b^d$c%!pxv4p
U*?Y:[x2iNe(XS>~y>esU|:lmDw=D2Na7*}]`wqHE3\Jm5D'
'-%1Ic2f{?|t|'\A)_WwS^, Please use ide.geeksforgeeks.org, 5 0 obj endstream endobj [0 0 720 540] >> << /Length 28 0 R /Filter /FlateDecode >> 9 0 obj
endobj
<< /Length 5 0 R /Filter /FlateDecode >> 21 0 obj 
<< /ProcSet [ /PDF /Text ] /ColorSpace << /Cs1 7 0 R /Cs2 8 0 R >> /Font << endstream
<< /Length 13 0 R /N 3 /Alternate /DeviceRGB /Filter /FlateDecode >> acknowledge that you have read and understood our, GATE CS Original Papers and Official Keys, ISRO CS Original Papers and Official Keys, ISRO CS Syllabus for Scientist/Engineer Exam, Multivariate Optimization and its Types Data Science, Multivariate Optimization Gradient and Hessian, Uni-variate Optimization vs Multivariate Optimization, Multivariate Optimization KKT Conditions, Multivariate Optimization with Equality Constraint, Python | Decision Tree Regression using sklearn, Boosting in Machine Learning | Boosting and AdaBoost, Learning Model Building in Scikit-learn : A Python Machine Learning Library, Linear Regression (Python Implementation). 5 0 obj
%])#-VZ)&MnIJiZgy_* T@SmAu^g6j4s. 27 0 obj CIFIeJ@z~xER]s7Id'a]"e endobj
<>/ProcSet[/PDF/Text/ImageB/ImageC/ImageI] >>/MediaBox[ 0 0 720 540] /Contents 20 0 R/Group<>/Tabs/S/StructParents 4>>
stream %
15 0 obj
16 0 obj << /Type /Page /Parent 3 0 R /Resources 17 0 R /Contents 15 0 R /MediaBox <>
<>/ProcSet[/PDF/Text/ImageB/ImageC/ImageI] >>/MediaBox[ 0 0 720 540] /Contents 15 0 R/Group<>/Tabs/S/StructParents 2>>
endobj Get access to ad-free content, doubt assistance and more! 1316 endobj
t]~Iv6W) |2]G4(6w$"AEvm[D;Vh[}N|3HS:KtxU'D;77;_"e?Y qx 
endstream
SOT^8JLQQId9V;;Ar gn>ebi^H{WW%qLPZ~Xy-jw3M5b>x:|FaY4_z7A1*0
w xTn0? xUoT>oR? <>/ExtGState<>/XObject<>/ProcSet[/PDF/Text/ImageB/ImageC/ImageI] >>/Annots[ 8 0 R] /MediaBox[ 0 0 612 792] /Contents 4 0 R/Group<>/Tabs/S/StructParents 0>>
rm:*}(OuT:NP@}(QK+#O14[ hu7>kk?kktqm6n-mR;`zv x#=\%
oYR#&?>n_;j;$}*}+(}'}/LtY"$].9%{_a]hk5'SN{_ t <>/XObject<>/ProcSet[/PDF/Text/ImageB/ImageC/ImageI] >>/MediaBox[ 0 0 720 540] /Contents 17 0 R/Group<>/Tabs/S/StructParents 3>>
<>
16 0 obj
D@)'}'JKcH,k! %f&aD2]]j0G@j<3:h>^2S2:(dt%uL6K!C,~Lj@n=e\FI7F2$HBMR)h}d endobj %PDF-1.5
xVn1}WTqV>@$J)3I)v|93gf<7n(5I1*_/''xc1kZk0}SVmngVt}&Z#%^lpLMaz-lkQGq[t>>,3?zLx',aU7o %
endobj endobj
endobj
20 0 obj
<>
fI8e*D$KfVHgo`g 
[0 0 720 540] >> endobj
3 0 obj
endobj /TT5 25 0 R /TT1 9 0 R >> >> (|k+0AE'=e47DU$/{q"C&2lT/A|P`mHm[5&3NHY(lUuD6J| ]2Ayv];"d>Mv;K17Uo!)16hmo6V. stream 23 0 obj 1 0 obj
Come write articles for us and get featured, Learn and code with the best industry experts. endobj 
q(q8cK8&A}=_M{D@4IAF7H>#Y:P9^? 12 0 obj
TpA(9>c+!W+%xk2YTmR,~\N0 /wjjPy>bUAhvvO3"f]q1`(Qls@_vbYAU@b"k6Q+)N)NzmkK,_2Oe"0'hIMsvcLq- C'dn=kog2s0;2f_=UAN#yFY \'4Nm@T(%aU2X4u'`SzwSI41pT]zhLhfm(pN,,jLkZ}Ee. stream 3 0 obj A1vjp zN6p\W
pG@ 
}oj1n_#WW WD.Ij 3[8CmMG 2D 4=3FNsyA:s$&9T#GuvOFLZg+;0Cu^f>R+{CX0 stream % 4.0,`
3p H.Hi@A> wUS1 /TT1 9 0 R >> >> 17 0 obj << /Length 23 0 R /Filter /FlateDecode >> 8 0 obj A-143, 9th Floor, Sovereign Corporate Tower, We use cookies to ensure you have the best browsing experience on our website. stream
7 0 obj
|Zo^ xwTS7" %z ;HQIP&vDF)VdTG"cEb PQDEk 5Yg} PtX4X\XffGD=H.d,P&s"7C$ 2 0 obj
<< %PDF-1.5
