{"segments": [{"id": 1, "seek": 4611, "start": 20.65, "end": 46.11, "text": "بسم الله الرحمن الرحيم احنا اليوم ان شاء الله بدنا نكمل الموضوع اللي فتحناه قبل هيكه في المحاضرات الماضية اللي هو ال artificial neural networks ال supervised learning باستخدام ال artificial neural networks كنا في المحاضرة الماضية حكينا عن اللي هو ال Perceptron وشوفنا قالية العمل تبعته", "tokens": [3555, 38251, 21984, 34892, 5016, 27842, 34892, 5016, 32640, 1975, 5016, 8315, 45595, 20498, 16472, 13412, 16606, 21984, 47525, 8315, 8717, 24793, 1211, 9673, 2407, 11242, 45367, 13672, 1829, 6156, 2655, 5016, 8315, 3224, 12174, 36150, 39896, 4117, 3224, 8978, 9673, 5016, 46958, 2288, 9307, 9673, 46958, 10632, 13672, 1829, 31439, 2423, 11677, 18161, 9590, 2423, 46533, 2539, 4724, 995, 14851, 9778, 3215, 10943, 2423, 11677, 18161, 9590, 9122, 8315, 8978, 9673, 5016, 46958, 25720, 9673, 46958, 10632, 11331, 4117, 1829, 8315, 18871, 13672, 1829, 31439, 2423, 3026, 1336, 2044, 4032, 8592, 38688, 8315, 12174, 6027, 10632, 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"end": 73.09, "text": "و آلية التعلم اللي هي مقصودة بالتعديل الأوزاني و بعدين كمان ايضا اطلعنا على ال multi-layered networks ال multi-layered networks اللي هي عبارة عن شبكة من ال perceptrons الشبكة هذه مهيكلة على أساس layers و ال layers كل layer فيها مجموعة من ال perceptrons بتغذي المجموعة اللي بعدها أو ال layer اللي بعدها", "tokens": [2407, 19753, 1211, 10632, 16712, 3615, 19528, 13672, 1829, 39896, 3714, 4587, 9381, 23328, 3660, 20666, 2655, 3615, 16254, 1211, 16247, 2407, 11622, 7649, 1829, 4032, 39182, 9957, 9122, 2304, 7649, 1975, 1829, 11242, 995, 1975, 9566, 1211, 3615, 8315, 15844, 2423, 4825, 12, 8376, 4073, 9590, 2423, 4825, 12, 8376, 4073, 9590, 13672, 1829, 39896, 6225, 3555, 9640, 3660, 18871, 13412, 3555, 4117, 3660, 9154, 2423, 43276, 13270, 25124, 3555, 4117, 3660, 29538, 3714, 3224, 1829, 28820, 3660, 15844, 5551, 3794, 32277, 7914, 4032, 2423, 7914, 28242, 4583, 8978, 11296, 3714, 7435, 2304, 2407, 27884, 9154, 2423, 43276, 13270, 39894, 17082, 8848, 1829, 9673, 7435, 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"probability": 0.9090169270833334}, {"start": 64.55, "end": 65.21, "word": " layers", "probability": 0.888671875}, {"start": 65.21, "end": 65.73, "word": " و", "probability": 0.693359375}, {"start": 65.73, "end": 65.85, "word": " ال", "probability": 0.68603515625}, {"start": 65.85, "end": 66.33, "word": " layers", "probability": 0.96044921875}, {"start": 66.33, "end": 66.77, "word": " كل", "probability": 0.7666015625}, {"start": 66.77, "end": 67.01, "word": " layer", "probability": 0.95263671875}, {"start": 67.01, "end": 67.27, "word": " فيها", "probability": 0.95458984375}, {"start": 67.27, "end": 67.77, "word": " مجموعة", "probability": 0.9681640625}, {"start": 67.77, "end": 67.95, "word": " من", "probability": 0.9873046875}, {"start": 67.95, "end": 68.09, "word": " ال", "probability": 0.9482421875}, {"start": 68.09, "end": 68.89, "word": " perceptrons", "probability": 0.933837890625}, {"start": 68.89, "end": 70.19, "word": " بتغذي", "probability": 0.94775390625}, {"start": 70.19, "end": 71.29, "word": " المجموعة", "probability": 0.9552734375}, {"start": 71.29, "end": 71.55, "word": " اللي", "probability": 0.943359375}, {"start": 71.55, "end": 71.95, "word": " بعدها", "probability": 0.930419921875}, {"start": 71.95, "end": 72.13, "word": " أو", "probability": 0.5986328125}, {"start": 72.13, "end": 72.27, "word": " ال", "probability": 0.89599609375}, {"start": 72.27, "end": 72.53, "word": " layer", "probability": 0.96435546875}, {"start": 72.53, "end": 72.71, "word": " اللي", "probability": 0.988525390625}, {"start": 72.71, "end": 73.09, "word": " بعدها", "probability": 0.9599609375}], "temperature": 1.0}, {"id": 3, "seek": 9720, "start": 74.08, "end": 97.2, "text": "وشوفنا آلية الآن التعلم في ال multilayer networks صح آلية التعلم المفصولة بها مرة أخرى اللي هي آلية تعديل الأوزان وشوفنا كيف بتختلف آلية تعديل الأوزان في ال output يرعنها في ال hidden layer صح الآن احنا بدنا", "tokens": [2407, 8592, 38688, 8315, 19753, 1211, 10632, 6024, 48506, 16712, 3615, 19528, 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ده كله لل iteration number two عشان تطلع أيش في الآخر الأوزان يعني في الآخر بدك تطلع صفحة زي هيك فيها أوزان جديدة", "tokens": [1211, 10721, 6156, 9778, 1211, 33546, 39896, 2423, 7649, 14578, 39896, 2423, 7649, 14578, 3714, 9566, 2304, 2407, 27884, 9154, 4117, 36632, 8592, 6055, 3794, 45865, 37279, 25708, 2423, 28820, 10943, 11778, 3224, 28242, 3224, 24976, 24784, 1230, 732, 6225, 8592, 7649, 6055, 9566, 1211, 3615, 36632, 8592, 8978, 6024, 95, 34740, 16247, 2407, 11622, 7649, 37495, 22653, 8978, 6024, 95, 34740, 47525, 4117, 6055, 9566, 1211, 3615, 20328, 5172, 5016, 3660, 30767, 1829, 39896, 4117, 8978, 11296, 34051, 11622, 7649, 10874, 16254, 41891], "avg_logprob": -0.1818933879627901, "compression_ratio": 1.6721311475409837, "no_speech_prob": 4.172325134277344e-07, "words": [{"start": 695.28, "end": 695.74, "word": "لأ", "probability": 0.6375732421875}, {"start": 695.74, "end": 697.4, "word": " فخلاص", "probability": 0.7960205078125}, {"start": 697.4, "end": 697.54, "word": " هي", 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و ال thresholds جديدة okay طيب هيك بنكون احنا القيل النظر الأخير على عملية ال back propagation learning واضح ليش اسمها back propagation لأن احنا بنحمل ال error لورا", "tokens": [6027, 20292, 47525, 11296, 6055, 7435, 5172, 43242, 11296, 13672, 1829, 31439, 2423, 24784, 16712, 7649, 1829, 8978, 8717, 11296, 10632, 2423, 24784, 16712, 7649, 1829, 1975, 1829, 8592, 8032, 2655, 30544, 12174, 32640, 3660, 16247, 2407, 11622, 7649, 25724, 16254, 41891, 4032, 2423, 14678, 82, 10874, 16254, 41891, 1392, 23032, 1829, 3555, 39896, 4117, 44945, 30544, 1975, 5016, 8315, 25062, 26895, 28239, 19913, 2288, 16247, 9778, 13546, 15844, 6225, 42213, 10632, 2423, 646, 38377, 2539, 4032, 46958, 5016, 32239, 8592, 24525, 2304, 11296, 646, 38377, 5296, 33456, 1975, 5016, 8315, 44945, 35571, 1211, 2423, 6713, 5296, 13063, 995], "avg_logprob": -0.2424999949336052, "compression_ratio": 1.8034188034188035, "no_speech_prob": 0.0, "words": [{"start": 715.85, "end": 716.41, "word": "اللي", "probability": 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"probability": 0.95556640625}], "temperature": 1.0}, {"id": 32, "seek": 80841, "start": 795.89, "end": 808.41, "text": "أحيانا ال network بتبقى ال output layer تبعتها فيها ال node واحدة فهو error واحد مصبوط أحيانا بيبقى ال layer الأخيرة بيبقى فيها عد تش", "tokens": [10721, 5016, 1829, 7649, 995, 2423, 3209, 39894, 3555, 4587, 7578, 2423, 5598, 4583, 6055, 3555, 34268, 11296, 8978, 11296, 2423, 9984, 36764, 24401, 3660, 6156, 3224, 2407, 6713, 36764, 24401, 3714, 9381, 3555, 2407, 9566, 5551, 5016, 1829, 7649, 995, 4724, 1829, 3555, 4587, 7578, 2423, 4583, 16247, 9778, 48923, 4724, 1829, 3555, 4587, 7578, 8978, 11296, 6225, 3215, 6055, 8592], "avg_logprob": -0.258184534216684, "compression_ratio": 1.5217391304347827, "no_speech_prob": 0.0, "words": [{"start": 795.89, "end": 796.65, "word": "أحيانا", "probability": 0.91162109375}, {"start": 796.65, "end": 796.73, "word": " ال", "probability": 0.366943359375}, {"start": 796.73, "end": 797.03, "word": " network", "probability": 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ربعنا ال errors هذه وجمعنا مربعاتهم بيطلع عني هنا some square error some square error يعني مقصود بمجموع مربعات ال errors تابعة من تابعة ال notes", "tokens": [2247, 279, 46599, 6027, 2655, 6027, 1829, 2423, 6713, 8978, 18871, 16254, 6713, 24976, 10721, 12610, 7578, 6713, 24976, 2655, 7649, 10632, 6225, 41891, 13603, 3714, 9381, 2304, 20498, 6156, 28814, 5016, 8315, 45164, 10874, 1829, 8315, 4724, 3555, 3794, 41193, 3660, 13412, 16254, 41891, 12602, 3555, 3615, 8315, 2423, 13603, 29538, 49610, 2304, 3615, 8315, 3714, 25513, 3615, 9307, 16095, 4724, 1829, 9566, 1211, 3615, 18871, 1829, 34105, 512, 3732, 6713, 512, 3732, 6713, 37495, 22653, 3714, 4587, 9381, 23328, 4724, 2304, 7435, 2304, 45367, 3714, 25513, 3615, 9307, 2423, 13603, 6055, 16758, 27884, 9154, 6055, 16758, 27884, 2423, 5570], "avg_logprob": -0.2398897063206224, "compression_ratio": 1.8712871287128714, "no_speech_prob": 5.960464477539063e-08, "words": [{"start": 809.09, "end": 809.77, "word": "notes", "probability": 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network هل تعلمت أو لا صح لأن كل ما عليه ال error هذا معناته هي لسه لسه بتخطط لسه بتخطط صح طب احنا في الأول ليش بنربّل نعمل تربيع ال error ليش ما ناخده زي ما هو قولنا هذا لأن بعض ال errors بتبقى بالموجب وبعض بالسالب لو جمعناهم هم ممكن يصفروا بعضهم", "tokens": [23189, 3732, 6713, 23758, 7251, 36520, 5016, 14739, 7251, 30544, 3714, 33604, 46309, 15844, 11933, 1829, 8592, 15844, 5551, 3215, 16606, 25124, 3555, 4117, 3660, 5551, 3215, 16606, 2423, 3209, 8032, 1211, 37279, 19528, 2655, 34051, 20193, 20328, 5016, 5296, 33456, 28242, 19446, 6225, 20292, 3224, 2423, 6713, 23758, 20449, 8315, 47395, 39896, 5296, 3794, 3224, 5296, 3794, 3224, 39894, 9778, 9566, 9566, 5296, 3794, 3224, 39894, 9778, 9566, 9566, 20328, 5016, 23032, 3555, 1975, 5016, 8315, 8978, 16247, 12610, 32239, 8592, 44945, 25513, 11703, 1211, 8717, 25957, 1211, 6055, 2288, 21292, 3615, 2423, 6713, 32239, 8592, 19446, 8717, 47283, 3215, 3224, 30767, 1829, 19446, 31439, 12174, 12610, 8315, 23758, 5296, 33456, 45030, 11242, 2423, 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أسرع أزيد ال alpha فإذا كان اختصر هذا ال linguistic كالتالي إذا كانت ال sign of sum of square errors ولا حد الاختصار", "tokens": [41185, 2423, 3732, 8978, 2408, 295, 3732, 13603, 7251, 3555, 4587, 7578, 41850, 9673, 5172, 32887, 11242, 5551, 3794, 2288, 3615, 5551, 11622, 25708, 2423, 8961, 6156, 28814, 15730, 25961, 1975, 46456, 9381, 2288, 23758, 2423, 43002, 9122, 6027, 2655, 6027, 1829, 11933, 15730, 25961, 2655, 2423, 1465, 295, 2408, 295, 3732, 13603, 49429, 11331, 3215, 42963, 46456, 9381, 9640], "avg_logprob": -0.3586065671483024, "compression_ratio": 1.5471698113207548, "no_speech_prob": 0.0, "words": [{"start": 1582.33, "end": 1582.59, "word": "في", "probability": 0.264404296875}, {"start": 1582.59, "end": 1583.19, "word": " ال", "probability": 0.51123046875}, {"start": 1583.19, "end": 1583.59, "word": " square", "probability": 0.27490234375}, {"start": 1583.59, "end": 1584.53, "word": " في", "probability": 0.29052734375}, {"start": 1584.53, "end": 1584.73, "word": " sum", 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