دورة التعليم الآلي Machine Learning

تعرف على كل ما يخص علم البيانات والتعلّم الآلي Machine Learning

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آخر تحديث : 24/01/2022

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عن الدورة

تعرف على كل ما يخص علم البيانات والتعلّم الآلي Machine Learning

محتوى الدورة

001 المقدمة00:07:50
002 ملاحظات سريعة00:02:14
003 بيئة عمل بايثون00:05:34
004 بيئة عمل R00:01:38
005 المعالجة المسبقة للبيانات00:05:32
006 المكتبات في بايثون00:03:57
007 المكتبات في لغة R100:02:33
008 استيراد الداتا بالبايثون00:06:32
009 ستيراد الداتا في R00:03:33
010 معالجة البيانات المفقودة في بايثون00:04:20
011 معالجة البيانات المفقودة في R00:08:21
012 معالجة البيانات النصية بالبايثون00:14:26
013 معالجة البيانات النصية في R00:06:28
014 فصل الداتا بالبايثون00:06:05
015 فصل الداتا في R00:09:15
016 Scaling in Python00:06:35
017 Scaling in R00:04:43
018 علم البيانات و الأعمال00:05:05
019 شرح simple linear regression00:07:15
020 شرح simple linear regression 200:03:16
021 SLR الخطوة الأولى بالبايثون00:12:01
022 SLR الخطوة الثانية بالبايثون00:05:38
023 SLR الخطوة الثالثة بالبايثون00:05:10
024 SLR الخطوة الرابعة بالبايثون00:07:58
025 SLR inR الخطوة الأولى00:09:41
026 SLR inR الخطوة الثانية00:03:54
027 SLR inR الخطوة الثالثة00:05:06
028 SLR inR الخطوةالرابعة00:10:02
029 مناقشة الداتاست00:02:59
030 مقدمة MLR00:04:08
031 Dummy Variable00:07:19
032 P Value00:01:53
033 Building a model00:10:05
034 MLR in Python Step100:11:01
035 MLR in Python Step200:03:36
036 MLR in Python Step300:02:21
037 التحضير لعمل BE00:05:12
038 BE00:08:39
039 Automatic BE00:01:57
040 MLR in R step100:08:34
041 MLR in R step 200:04:37
042 MLR in R step 300:04:17
043 Automatic BE in R00:08:19
044 Polynomial Regression00:07:07
045 مجموعة البيانات00:03:30
046 Poly Reg in python step100:08:25
047 Poly Reg in python step 200:09:47
048 Poly Reg in python step 300:13:51
049 Poly Reg in python step 400:05:00
050 Poly Reg in R step 100:06:18
051 Poly Reg in R step 200:08:36
052 Poly reg in R step 300:09:55
053 Poly Reg in R step 400:05:43
054 Support Vector Regressor00:07:39
055 SVR in python00:18:16
056 SVR in R00:13:34
057 Decision Tree Introduction00:05:40
058 Decision Tree in python00:08:59
059 Decision Tree in R00:11:41
060 Decision Tree Introduction00:05:40
061 Decision Tree in python00:08:59
062 Decision Tree in R00:11:41
063 Random Forest Introduction00:03:43
064 Random Forest in Python00:17:29
065 Random Forest in R00:15:47
066 Which model00:03:09
067 Continuous Uniform Distributions00:06:51
068 Binomial Distribution00:10:03
069 Poisson Distribution00:07:11
070 Normal Distribution00:05:37
071 T Distribution00:07:17
072 Hypothesis Testing00:08:14
073 Web Scrapping 100:10:47
074 Web Scrapping 200:10:42
075 Python Part100:08:54
076 Python Part200:07:26
077 Python Part300:08:43
078 Python Part400:08:27
079 Kernel SVM in Python00:14:22
080 Kernel SVM in R00:05:31
081 Naive Bayes Introduction00:04:48
082 Naive Bayes in Python00:12:20
083 Naive Bayes in R00:09:23
084 DT Classification Introduction00:04:41
085 DT Classifier in Python00:15:06
086 DT Classifier in R00:10:47
087 Random Forest00:02:59
088 Random Forest classifier in Python00:13:38
089 Random Forest classifier in R00:12:56
090 Evaluating Performance00:07:29
091 كيف أختار المودل؟00:03:26
092 Clustering Introduction00:04:31
093 K means Algorithms00:04:29
094 K means in Python00:24:06
095 K means in R00:18:54
096 Hierarchical Clustering introduction00:06:39
097 HC in Python step 100:08:19
098 HC in Python step 200:06:49
099 HC in R step 100:07:16
100 HC in R step 200:06:34
101 Apriori Algorithms intro00:04:59
102 Apriori Algorithms step 1 in Python00:09:10
103 Apriori Algorithms step 2 in Python00:08:14
104 Apriori Algorithms step 3 in Python00:07:43
105 Apriori Algorithms step 1 in Pythonn00:07:12
106 Apriori Algorithms step 2 in Pythonn00:04:40
107 Apriori Algorithms step 3 in Pythonn00:03:34
108 Elcat Model00:02:13
109 Elcat Model in R00:08:03
110 Reinforcement Learning00:02:35
111 Multi Armed Bandit Problem00:08:04
112 Upper Confidence Bound00:06:58
113 USB step 1 in Python00:08:03
114 UCB step 2 in Python00:16:54
115 UCB step 3 in Python00:08:23
116 UCB step 4 in Python00:03:10
117 UCB step 1 in R00:08:54
118 UCB step 2 in R00:14:52
119 UCB step 3 in R00:08:16
120 UCB step 4 in R00:03:03
121 Thompson Sampling Alg00:03:58
122 Thompson in Python00:13:17
123 Thompson in R00:15:05
124 Natural Language Processing Intro00:07:58
125 NLP step 1 in Python00:09:04
126 NLP step 2 in Python00:09:41
127 NLP step 3 in Python00:01:22
128 NLP step 4 in Python00:08:41
129 NLP step 5 in Python00:10:08
130 NLP step 6 in Python00:07:04
131 NLP step 7 in Python00:04:11
132 NLP step 8 in Python00:09:55
133 NLP step 1 in R00:07:19
134 NLP step 2 in R00:04:36
135 NLP step 3 in R00:03:01
136 NLP step 4 in R00:02:08
137 NLP step 5 in R00:02:12
138 NLP step 6 in R00:03:46
139 NLP step 7 in R00:03:36
140 NLP step 8 in R00:02:35
141 NLP step 9 in R00:09:36
142 NLP step 10 in R00:07:23
143 Deep Learning100:04:36
144 Deep Learning 200:08:21
145 Business Problem Descriptive00:03:22
146 Artificial Nerual Network Steps00:03:24
147 The Neuron00:11:41
148 The Activiation Function00:05:12
149 NN works00:07:09
150 NN learrn00:10:52
151 Gradient Descent00:07:08
152 Stochostic Gradient Descent00:03:39
153 backprobacation00:02:49
154 ANN IN Python step 100:08:57
155 ANN IN Python step 200:18:10
156 ANN IN Python step 300:04:20
157 ANN IN Python step 400:05:37
158 ANN IN Python step 500:02:32
159 ANN IN Python step 600:03:06
160 ANN IN Python step 700:04:10
161 ANN IN Python step 800:05:06
162 ANN IN Python step 900:06:25
163 ANN IN Python step 1000:05:19
164 ANN in R step 100:08:48
165 ANN in R step 200:04:15
166 ANN in R step 300:05:54
167 ANN in R step 400:07:12
168 Convloutional Neural Networks00:03:54
169 what are CNN00:09:27
170 step1 Convloution00:05:38
171 step 2 b RelU00:03:42
172 step 2 Pooling00:05:09
173 step 3 Flattning00:02:07
174 step 4 Fully Connected00:07:23
175 Summary00:03:07
176 Softmax Cross Entropy00:04:07
177 CNN in Python step 100:05:33
178 CNN in Python step 200:05:16
179 CNN in Python step 300:02:07
180 CNN in Python step 400:03:46
181 CNN in Python step 500:02:34
182 CNN in Python step 600:05:17
183 CNN in Python step 700:04:01
184 CNN in Python step 800:03:06
185 CNN in Python step 900:12:06
186 CNN in Python step 1000:02:04
187 CNN in R00:01:16
188 DR Introduction00:03:20
189 PCA Intro00:05:07
190 PCA in Python step 100:07:05
191 PCA in Python step 200:09:51
192 PCA in Python step 300:05:44
193 PCA in R step 100:07:50
194 PCA in R step 200:07:31
195 PCA in R step 300:10:05
196 LDA Intro00:05:03
197 LDA in Python00:08:30
198 LDA in R00:13:34
199 KernelPCA in Python00:11:33
200 KernelPCA in R00:17:49
201 Model Selection XGBoost Intro00:05:11
202 K cross validation in Python00:12:58
203 K cross validation in R00:24:56
204 Grid Search in Python step 100:07:34
205 Grid Search in Python step 200:07:12
206 Grid Search in R00:10:06
207 XGBoost in Python step 100:05:42
208 XGBoost in Python step 200:07:23
209 XGBoost in R00:10:21
210 The End00:02:20

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