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Mathematics, Probability & Statistics for Machine Learning

Learn Maths, Probability and Statistics for Data Science, Artificial Intelligence (AI), Machine Learning & Deep Learning

99masterclass

Summary

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£14 inc VAT
Study method
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Duration
36.8 hours · Self-paced
Qualification
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Certificates
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Overview

This course is updated frequently with new lessons, projects, and resources!

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Understand the Essential Mathematics for Machine Learning

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Curriculum

47
sections
645
lectures
36h 48m
total

    • 1: !Importance of Set TheoryFINAL Preview 00:42
    • 2: 1_WhatIsSet_SetFINAL Preview 05:15
    • 3: 2a_Uniiversal vs SubsetFINAL 02:00
    • 4: 2b_Proper and Improper SubsetFINAL 08:05
    • 5: 3_Singleton Set 01:24
    • 6: 4_Null orEmpty SetFINAL 01:42
    • 7: 5_Power Sets 05:43
    • 8: 6_Equal vs Equivalent SetsFINAL 01:26
    • 9: 7_Set Builder NotationFINAL 03:55
    • 10: 8_Cardality of a SetFINAL 01:17
    • 11: 9_SetOperation_Element_Cardinality_Union_Inetersect_Complement_Disjoint_NonDisjo 12:20
    • 12: 10_Laws of SetFINAL Preview 11:22
    • 13: 11_Challenge & SolutionFINAL 01:25
    • 14: 12_Challenge & SolutionFINAL 01:16
    • 15: 13_Challenge & Solution 01:19
    • 16: 14_Finite vs InfiniteFINAL 02:11
    • 17: 15_Range & Domain SetsFINAL 08:58
    • 18: 16_NumberSet---prime-odd-even-multiples-odd-prime-divibility 05:18
    • 19: 16b_General_Number_SetFINAL 07:58
    • 20: 17_Challenges & SolutionFINAL 01:40
    • 21: 18_Challenges & Solution-Complement Of UnionSetFINAL 02:10
    • 22: 19_Challenges & Solution-Elements of InersectionFINAL 06:39
    • 23: 20_Challenges & Solution 03:49
    • 24: 21_Challenges & SolutionFINAL 01:20
    • 25: 22_Challenges & SolutionFINAL 00:54
    • 26: 23_Challenges & SolutionFINAL 02:11
    • 27: 24_Venn DiagramFINAL 03:42
    • 28: 25_Challenge_and_SolutionFINAL 00:42
    • 29: 26_Challenge_and_SolutionFINAL 02:54
    • 30: 27_Challenge_and_SolutionFINAL 02:21
    • 31: 28_Challenge_and_SolutionFINAL 01:03
    • 32: 29_Challenge_and_SolutionFINAL 03:12

    • 33: ! Importance of Combinatorics for Machine Learning 01:07
    • 34: !Importance of Combinatorics 02:16
    • 35: 1_Factorial_Intro 03:07
    • 36: 2 Factorial - Exercise & Solution 01:11
    • 37: 2_Challenge & Solution 02:01
    • 38: 3 Permutation 02:01
    • 39: 3_Permutaion 04:02
    • 40: 4 Combination 02:16
    • 41: 4_Combination 04:45
    • 42: 5 Exercise & Solution 02:19
    • 43: 5_Challenge & Solution 04:00
    • 44: 6 Exercise & Solution 02:11
    • 45: 6_Challenge & Solution 04:37
    • 46: 7 Exercise & Solution 00:52
    • 47: 7_Challenge & Solution 04:38
    • 48: 8 Exercise & Solution 01:36
    • 49: 8_Challenge & Solution 02:49
    • 50: 9 Exercise & Solution 01:46
    • 51: 9_Challenge & Solution 03:17
    • 52: 10 Exercise & Solution 04:53
    • 53: 10_Challenge & Solution 11:31
    • 54: 11 Exercise & Solution 00:25
    • 55: 11_Challenge & Solution 00:56
    • 56: 12 Exercise & Solution 03:51
    • 57: 12_Important INSIGHT 09:39
    • 58: 13 Exercise & Solution 05:03
    • 59: 13_Challenge & Solution 09:14
    • 60: 14 Exercise & Solution 03:38
    • 61: 14_Challenge & Solution 09:23
    • 62: 15 Exercise & Solution 05:35
    • 63: 15_Challenge & Solution 11:38
    • 64: 16 Exercise & Solution 01:07
    • 65: 16_Challenge & Solution 01:35
    • 66: 17_INSIGHT 16:07
    • 67: 17_INSIGHTFinal 05:10
    • 68: 18 Exercise & Solution 00:54
    • 69: 18_Challenge & Solution 02:15
    • 70: 19 Exercise & Solution 01:05
    • 71: 19_Challenge & Solution 01:33
    • 72: 20 Exercise & Solution 03:17
    • 73: 20_Challenge & Solution 04:27
    • 74: 20c_Challenge & Solution 02:28

    • 75: ! Importance of Probability 00:53
    • 76: !Importance of Probability 02:46
    • 77: 1 What is Probability 02:28
    • 78: 1Redooo_Introduction to Probability 04:57
    • 79: 2 Basic Terms in Probability 07:43
    • 80: 2 Probability Terms 15:58
    • 81: 3 General Formula 05:16
    • 82: 3 Possible Outcome 10:34
    • 83: 4 Challenge & Solution 04:12
    • 84: 4 Exercise & Solution 02:20
    • 85: 6 Exercise & Solution 00:52
    • 86: 7 Exercise & Solution 02:27
    • 87: 8 Challenge & Solution 02:33
    • 88: 8 Exercise & Solution 01:37
    • 89: 9 Challenge & Solution 01:38
    • 90: 9 Exercise & Solution 01:00
    • 91: 10 Challenge & Solution 02:05
    • 92: 10 Exercise & Solution 00:54
    • 93: 11 Challenge & Solution 02:34
    • 94: 11 Exercise & Solution 01:31
    • 95: 12 Challenge & Solution 02:17
    • 96: 12 Exercise & Solution 01:41
    • 97: 13 Challenge & Solution 00:35
    • 98: 13 Exercise & Solution 00:22
    • 99: 15 Challenge & Solution 02:09
    • 100: 15 Exercise & Solution 00:58

    • 101: 1_Intro_theoretical probability 02:40
    • 102: 1_Intro_theoretical probabilityFINAL 01:05
    • 103: 2_Challenge & Solution.mp4 03:34
    • 104: 2_Challenge & SolutionFINAL 02:02
    • 105: 3_Challenge & Solution.mp4.mp4 04:09
    • 106: 3_Challenge & SolutionFINAL 01:17
    • 107: 4_Challenge & Solution.mp4.mp4.mp4 03:50
    • 108: 4_Challenge & SolutionFINAL 02:08
    • 109: 5_Challenge & Solution.mp4.mp4.mp4 02:13
    • 110: 5_Challenge & SolutionFINAL 01:21
    • 111: 6_Challenge & Solution.mp4.mp4.mp4 02:21
    • 112: 6_Challenge & SolutionFINAL 01:03
    • 113: 7_Challenge & Solution.mp4.mp4.mp4 01:43
    • 114: 7_Challenge & SolutionFINAL 01:04
    • 115: 8_Challenge & Solution.mp4.mp4.mp4 01:11
    • 116: 8_Challenge & SolutionFINAL 00:44

    • 117: 1_intro_I 02:01
    • 118: 1_intro_IFINAL 01:01
    • 119: 1_intro_II 01:42
    • 120: 2_Challenge & Solution.mp4 05:13
    • 121: 2_Challenge & SolutionFINAL 02:25
    • 122: 3_Challenge & Solution.mp4 01:41
    • 123: 3_Challenge & SolutionFINAL 01:03
    • 124: 4_Challenge & Solution 01:37
    • 125: 4_Challenge & SolutionFINAL 01:05
    • 126: 5_Challenge & Solution.mp4 01:41
    • 127: 5_Challenge & SolutionFINAL 01:01
    • 128: 6_Challenge & Solution.mp4 02:09
    • 129: 6_Challenge & SolutionFINAL 01:02

    • 130: 1_Addition Rules - Mutual and Non 06:00
    • 131: 1_Addition Rules - Mutual and NonFINAL 03:24
    • 132: 2_Examples of the two 06:31
    • 133: 2_Examples of the twoFINAL 00:09
    • 134: 3_ Challenge & Solution_ME 02:31
    • 135: 3_ Challenge & Solution_MEFINAL 01:08
    • 136: 4_ Challenge & Solution_ME 03:22
    • 137: 4_ Challenge & Solution_MEFINAL 02:02
    • 138: 5_ Challenge & Solution_ME 01:17
    • 139: 5_ Challenge & Solution_MEFINAL 02:14
    • 140: 6_ Challenge & Solution_ME.mp4 02:11
    • 141: 6_ Challenge & Solution_MEFINAL 01:03
    • 142: 7_ Challenge & Solution_ME.mp4 01:56
    • 143: 7_ Challenge & Solution_MEFINAL 00:53
    • 144: 8_ Challenge & Solution_ME.mp4 02:30
    • 145: 8_ Challenge & Solution_MEFINAL 01:50
    • 146: 9_ Challenge & Solution_ME.mp4 05:17
    • 147: 9_ Challenge & Solution_MEFINAL 02:38
    • 148: 10_ Challenge & Solution_ME 04:50
    • 149: 10_ Challenge & Solution_MEFINAL 02:18

    • 150: 1_Multiplication Dependent and Independent Events 06:03
    • 151: 1_Multiplication Dependent and Independent EventsFINAL 02:30
    • 152: 2_Challenge & Solution 01:47
    • 153: 2_Challenge & SolutionFINAL 00:57
    • 154: 3_Challenge & Solution 09:07
    • 155: 3_Challenge & SolutionFinal 04:55
    • 156: 4_Challenge & Solution 03:18
    • 157: 4_Challenge & SolutionFINAL 01:26
    • 158: 5_Challenge & Solution 02:33
    • 159: 5_Challenge & SolutionFINAL 01:44
    • 160: 6_Challenge & Solution 02:25
    • 161: 6_Challenge & SolutionFINAL 01:46
    • 162: 7_Challenge & Solution 02:21
    • 163: 7_Challenge & SolutionFINAL 01:34

    • 164: 1_Challenge & Solution 03:22
    • 165: 1_Challenge & SolutionFINAl 01:30
    • 166: 2_Challenge & Solution 03:15
    • 167: 2_Challenge & SolutionFINAL 02:09
    • 168: 3_Challenge & Solution 03:31
    • 169: 3_Challenge & SolutionFINAL 01:54
    • 170: 4_Challenge & Solution 02:57
    • 171: 4_Challenge & SolutionFINAL 01:42
    • 172: 5_Challenge & Solution 01:41
    • 173: 5_Challenge & SolutionFINAL 01:02
    • 174: 6_Challenge & Solution 01:43
    • 175: 6_Challenge & SolutionFINAL 01:13
    • 176: 7_Challenge & Solution 02:13
    • 177: 7_Challenge & SolutionFINAL 01:41
    • 178: 8_Challenge & Solution 02:38
    • 179: 8_Challenge & SolutionFINAL 01:41
    • 180: 9_Challenge & Solution 02:47
    • 181: 9_Challenge & SolutionFINAL 01:56
    • 182: 10_Challenge & Solution 07:50
    • 183: 10_Challenge & SolutionFINAL 04:04
    • 184: 11_Challenge & Solution 01:26
    • 185: 11_Challenge & SolutionFINAL 01:00
    • 186: 12_Challenge & Solution 03:30
    • 187: 12_Challenge & SolutionFINAL 01:51
    • 188: 13_Challenge & Solution 07:59
    • 189: 13_Challenge & SolutionFINAL 07:22
    • 190: 13b_Challenge & Solution 03:31
    • 191: 14_Challenge & Solution 10:22
    • 192: 14_Challenge & SolutionFINAL 05:17
    • 193: 15_Challenge & Solution 01:31
    • 194: 15_Challenge & SolutionFINAL 00:58
    • 195: 16_Challenge & Solution.mp4 02:09
    • 196: 16_Challenge & SolutionFINAL 01:27
    • 197: 17_Challenge & Solution.mp4 03:43
    • 198: 17_Challenge & SolutionFINAL 01:33
    • 199: 18_Challenge & Solution.mp4 02:28
    • 200: 18_Challenge & SolutionFINAL 01:38
    • 201: 19_Challenge & Solution.mp4 02:48
    • 202: 19_Challenge & SolutionFINAL 01:37
    • 203: 20_Challenge & Solution.mp4 02:31
    • 204: 20_Challenge & SolutionFINAL 01:30
    • 205: 23_Challenge & SolutionNotYETEDITED.mp4 06:52

    • 206: 1_Random Variable 08:41
    • 207: 1_Random VariableFINAL 01:50
    • 208: 2_Discrete and Continuous VariableEdite Please 08:32
    • 209: 3_Binomial Propability Distribution 18:32
    • 210: 3_Binomial Propability DistributionFINAL 04:01
    • 211: 4_Challenge & Solution 17:00
    • 212: 4_Challenge & SolutionFINAL 05:48
    • 213: 5_Challenge & Solution 11:00
    • 214: 5_Challenge & SolutionFINAL 06:35
    • 215: 6_Challenge & Solution..FINAL 03:10
    • 216: 6_Challenge & Solution 05:33
    • 217: 7_Challenge & Solution 06:35
    • 218: 7_Challenge & SolutionFINAL 03:42
    • 219: 8_Challenge & Solution 04:49
    • 220: 8_Challenge & SolutionFINAL 02:15
    • 221: 9_Challenge & Solution 03:50
    • 222: 9_Challenge & SolutionFINAL 02:10
    • 223: 10_Poisson Distribution 06:10
    • 224: 10_Poisson DistributionFINAL 01:39
    • 225: 11_Challenge & Solution..FINAL 06:37
    • 226: 11_Challenge & Solution 11:58
    • 227: 13_Normal Distribution 16:54
    • 228: 13_Normal DistributionFINAL 05:52
    • 229: 14-Z-Score 05:06
    • 230: 14-Z-ScoreFINAL 01:29
    • 231: 16_Challenge & Solution Normal 08:56
    • 232: 16_Challenge & Solution NormalFINAL 04:45
    • 233: 17_Challenge & Solution Normal 11:41
    • 234: 17_Challenge & Solution NormalFINAL 03:12
    • 235: 18_Skeweness 07:26
    • 236: 18_SkewenessFINAL 02:12
    • 237: 19_Kurtosis 01:30
    • 238: 19_KurtosisFINAL 01:30
    • 239: 20_T Distribution 07:04
    • 240: 20_T DistributionFINAL 02:51

    • 241: 1-Conditional Probability 03:01
    • 242: 1-Conditional ProbabilityFINAL 01:21

    • 243: 1-Theorem of Total Probability 06:20
    • 244: 1-Theorem of Total Probability_II 14:35
    • 245: 1-Theorem of Total ProbabilityFINAL 07:36
    • 246: 2-Theorem of Total Probability Exceptional Case 12:07
    • 247: 2-Theorem of Total Probability Exceptional CaseFINAL 05:26

    • 248: 1_Bayes' Theorem 17:55
    • 249: 1_Bayes' TheoremFINAL 06:39
    • 250: 2_Bayes' Theorem_Exceptional 05:18
    • 251: 2_Bayes' TheoremFINAL 00:24

    • 252: 1_Decision Tree of Probability 15:32
    • 253: 1_Decision Tree of ProbabilityFINAL 08:10
    • 254: 2_Exercise and Solution Decision Dependent 04:55
    • 255: 2_Exercise and Solution Decision DependentFINAL 02:06
    • 256: 3_Exercise and Solution Decision Dependent 06:44
    • 257: 3_Exercise and Solution Decision DependentFINAL 03:17
    • 258: 4_Exercise and Solution Decision Total Probability 07:59
    • 259: 4_Exercise and Solution Decision Total ProbabilityFINAL 02:40
    • 260: 5_Exercise and Solution 03:38
    • 261: 5_Exercise and SolutionFINAL 01:23
    • 262: 6_Bayes Exercise 06:40
    • 263: 6_Bayes ExerciseFINAL 06:40
    • 264: 8_Total Probability Exercise 05:10
    • 265: 8_Total Probability ExerciseFINAL 02:48
    • 266: 9_Total Probability Exercise 05:17
    • 267: 9_Total Probability Exercise FINAL 02:49

    • 268: 21_importance of probability 08:48
    • 269: 21_importance of probabilityFINAL 02:18

    • 270: !Importance of Statistics 01:06
    • 271: !Importance of StatisticsFINAL 00:37
    • 272: 1_Introduction to Statistics 18:22
    • 273: 1_Introduction to StatisticsFINAL 01:34
    • 274: Frequency and tally 03:03
    • 275: Frequency and tallyFINAL 02:29
    • 276: PopulationVSsampleFINAL 01:28
    • 277: RawData and Array 00:54
    • 278: RawData and ArrayFINAL 00:50

    • 279: 2_Mean 04:00
    • 280: 2_MeanFINAL 01:45
    • 281: 3_Mean example 01:48
    • 282: 3_Mean exampleFINAL 00:59
    • 283: 4_Mean example 01:52
    • 284: 4_Mean exampleFINAL 01:22
    • 285: 5_Mean example 02:19
    • 286: 5_Mean exampleFINAL 01:28
    • 287: 6_Mean example 01:50
    • 288: 6_Mean exampleFINAL 00:54
    • 289: 7_Mean example 01:05
    • 290: 7_Mean exampleFINAL 00:42
    • 291: 8_Mean example 02:43
    • 292: 8_Mean exampleFINAL 01:42
    • 293: 9_Mean example 03:20
    • 294: 9_Mean exampleFINAL 01:57
    • 295: 10_Mean example 02:11
    • 296: 10_Mean exampleFINAL 01:22

    • 297: 1_Weighted Mean 01:53
    • 298: 1_Weighted MeanFINAL 01:06
    • 299: 2_Example 1 05:20
    • 300: 2_Example 1FINAL 02:24
    • 301: 3_Example 2 03:14
    • 302: 3_Example 2FINAL 01:49

    • 303: 1_Basic Properties of Mean 16:01
    • 304: 1_Basic Properties of MeanFINAL 07:17
    • 305: Example 1 02:13
    • 306: Example 1_FINAL 01:05
    • 307: Example 2 01:11
    • 308: Example 2FINAL 00:29
    • 309: Example 3 03:45
    • 310: Example 3_FINAL 02:23
    • 311: Example 4 01:03
    • 312: Example 4FINAL 00:42
    • 313: Example 5 00:47
    • 314: Example 5FINAL 00:18
    • 315: Example 6 05:01
    • 316: Example 6FINAL 02:27

    • 317: 1_intro 01:44
    • 318: 1_introFINAL 00:53
    • 319: Example 1 02:54
    • 320: Example 1FINAL 02:01
    • 321: Example 2 02:46
    • 322: Example 2FINAL 01:04
    • 323: Example 3 02:06
    • 324: Example 3FINAL 01:19

    • 325: 1_intro 03:15
    • 326: 1_introFINAL 02:03
    • 327: Example 1 01:05
    • 328: Example 1FINAL 00:26

    • 329: 1_Introduction 05:59
    • 330: 1_IntroductionFINAL 02:26
    • 331: Example 1 02:04
    • 332: Example 1FINAL 01:09
    • 333: Example 2 02:09
    • 334: Example 2FINAL 01:13
    • 335: Example 3 01:45
    • 336: Example 3FINAL 00:56

    • 337: 1_mode intro 01:54
    • 338: 1_mode introFINAL 00:58
    • 339: Example_1 00:20
    • 340: Example_1FINAL 00:16
    • 341: Example_2 00:34
    • 342: Example_2FINAL 00:19

    • 343: Example 1 01:07
    • 344: Example 1FINAL 00:25
    • 345: Example 2 00:29
    • 346: Example 2FINAL 00:18

    • 347: 9_Measurement of SpreadFINAL 00:34
    • 348: Meaning 01:13

    • 349: 1_What is range 00:22
    • 350: 1_What is rangeFINAL 00:14
    • 351: Example 1 01:38
    • 352: Example 1nFINAL 00:53
    • 353: Example 2 00:40
    • 354: Example 2FINAL 00:25
    • 355: Example 3 00:50
    • 356: Example 3FINAL 00:31

    • 357: 1 Understanding Mean Deviation 04:54
    • 358: 1 Understanding Mean DeviationFINAL 03:27
    • 359: 2Example 1 03:27
    • 360: 2Example 1FINAL 01:42
    • 361: 3Example 2 03:40
    • 362: 3Example 2FINAL 00:58
    • 363: 4_mean deviation for frequency distributiom 04:40
    • 364: 4_mean deviation for frequency distributiomFINAL 00:18

    • 365: 1-Undersanding Variance and Standard Deviation 03:50
    • 366: 1-Undersanding Variance and Standard DeviationFINAL 02:36
    • 367: 2_Basic Properties of variance and standard deviation 06:39
    • 368: 2_Basic Properties of variance and standard deviationFINAL 01:59
    • 369: Example 1 02:59
    • 370: Example 1FINAL 00:45
    • 371: Example 2 02:10
    • 372: Example 2FINAL 01:11
    • 373: Example 4 01:09
    • 374: Example 4FINAL 00:40
    • 375: Example 5 04:06
    • 376: Example 5l_FINAL 03:03
    • 377: Example 6 02:45
    • 378: Example 6FINAL 01:31
    • 379: Example 8 06:20
    • 380: Example 8FINAL 02:27
    • 381: Example 9 04:31
    • 382: Example 9FINAL 02:44
    • 383: Example 10 02:40
    • 384: Example 10FINAL 01:15
    • 385: Example 11 02:49
    • 386: Example 11FINAL 01:52
    • 387: Example 12 08:57
    • 388: Example 12FINAL 05:46

    • 389: 1-Correlation 07:17
    • 390: 1-CorrelationFINAL 04:54
    • 391: 2_correlation is not causation 14:22

    • 392: !_Regression collinearity 13:34
    • 393: 1_RegressionFINAL 06:16
    • 394: 2_CollinearityFINAL 03:12

    • 395: 1_Understanding Pearson and Spearman Correlation Cofficient 11:10
    • 396: 1_Understanding Pearson and Spearman Correlation CofficientFINAL 01:38
    • 397: 2_Spearman 01:04
    • 398: 2_SpearmanFINAL 00:46
    • 399: 3_Pearson 01:07
    • 400: 3_PearsonFINAL 00:51
    • 401: 4_Example Spearman 11:44
    • 402: 4_Example SpearmanFINAL 06:11
    • 403: 5_Example Pearson 09:55
    • 404: 5_Example PearsonFINAL 04:54

    • 405: 1_Regression Error Metrics 12:15
    • 406: 1_Regression Error MetricsFINAL 04:47
    • 407: 2_Mean Squared Error 10:26
    • 408: 2_Mean Squared ErrorFINAL 05:12
    • 409: 3_Mean Absolute Error 02:43
    • 410: 3_Mean Absolute ErrorFINAL 01:13
    • 411: 4_Root Mean Squared Error 01:54
    • 412: 4_Root Mean Squared ErrorFINAL 00:22
    • 413: 5_R-Squared or Coefficient of Determination 09:24
    • 414: 5_R-Squared or Coefficient of DeterminationFINAL 02:36
    • 415: 6_Adjusted R Squared 01:56
    • 416: 6_Adjusted R SquaredFINAL 00:58
    • 417: 7_Summary 06:22
    • 418: 7_SummaryFINAL 02:24

    • 419: ! Importance of Logarithms to Machine learning 03:35
    • 420: 1 Laws of Indices 08:13
    • 421: 1_Laws of Indices 15:07
    • 422: 2 Exercise and Solution 02:19
    • 423: 2_Laws of Indices_Ex 04:36
    • 424: 3 Exercise and Solution 01:20
    • 425: 3_Laws of Indices_Ex 02:43
    • 426: 3_Laws of Indices_ExFINAL 01:20
    • 427: 4 Exercise and Solution 01:31
    • 428: 4_Laws of Indices 02:59
    • 429: 5 Exercise and Solution 02:03
    • 430: 5_Laws of Indices_Ex 04:15
    • 431: 6 Exercise and Solution 02:14
    • 432: 6_Laws of Indices_Ex 03:17
    • 433: 7 Exercise and Solution 00:37
    • 434: 7_Laws of Indices_Ex 01:05
    • 435: 8 Exercise and Solution 01:53
    • 436: 8_Indices in algebraic terms and powers 05:42
    • 437: 9 Exercise and Solution 01:37
    • 438: 9_Indices in algebraic terms and powers_Ex 02:45
    • 439: 10 Exercise and Solution 00:44
    • 440: 10_Indices in algebraic terms and powers_Ex 02:36
    • 441: 11 Exercise and Solution 01:16
    • 442: 11_Indices in algebraic terms and powers_Ex 02:39
    • 443: 12 Indices Inoving Equations 00:58
    • 444: 12_Indices Involving Equation 01:51
    • 445: 13 Exercise and Solution 02:01
    • 446: 13_Indices Involving Equation_Ex 03:23
    • 447: 14 Exercise and Solution 02:40
    • 448: 14_Indices Involving Equation_Ex 04:58
    • 449: 15 Exercise and Solution 00:36
    • 450: 15_Indices Involving Equation_Ex.mp4 01:08
    • 451: 16 Exercise and Solution 01:34
    • 452: 16_Indices Involving Equation_Ex.mp4 04:19
    • 453: 17 Exercise and Solution 01:48
    • 454: 17_Indices Involving Equation_Ex.mp4 01:48
    • 455: 18 Exercise and Solution 02:28
    • 456: 18_Indices Involving Equation_Ex.mp4 04:04
    • 457: 1 Introduction to Logarithm 2 03:29
    • 458: 1 Introduction to Logarithm 08:44
    • 459: 2 First Law of Logarithm 2 01:39
    • 460: 2 First Law of Logarithm 04:08
    • 461: 3 Second Law of Logarithm 2 01:25
    • 462: 3 Second Law of Logarithm 03:04
    • 463: 3!_3 - 8Laws of Logaritthm from 3 to 8RAW 14:57
    • 464: 4 Third Law of Logarithm 01:44
    • 465: 5 Fourth Law of Logarithm 00:32
    • 466: 6 Fifth Laws of Logarithm 00:25
    • 467: 7 Sixth Laws of Logarithm 00:42
    • 468: 8 Seventh Law of Logarithm 01:04
    • 469: 9 Eight Law of Logarithm 02:03
    • 470: 10 Summary of the laws of logarithms 02:14
    • 471: 10 Summary of the laws of logarithms 04:24
    • 472: 11 Logarithms 00:30
    • 473: 11 Logarithms_Ex 01:02
    • 474: 12 Logaritghms 00:57
    • 475: 12 Logaritghms_Ex 01:56
    • 476: 13 Logaritghms 01:30
    • 477: 13 Logaritghms_Ex 02:24
    • 478: 14 Logaritghms 01:08
    • 479: 14 Logaritghms_Ex 02:22
    • 480: 15 Logaritghms 00:29
    • 481: 15 Logaritghms_Ex 00:32
    • 482: 16 Logaritghms 01:16
    • 483: 16 Logaritghms_Ex 02:50
    • 484: 17 Logaritghms 00:53
    • 485: 17 Logaritghms_Ex 01:49
    • 486: 18 Logaritghms 00:39
    • 487: 18 Logaritghms_Ex 01:37
    • 488: 19 Logaritghms 01:09
    • 489: 19 Logaritghms_Ex 03:33
    • 490: 20 Logaritghms 01:02
    • 491: 20 Logaritghms_Ex 02:53
    • 492: 21 Change Base 04:50
    • 493: 21 Change BaseFINAL 01:48
    • 494: 22 Exercise and Solution Raw 05:19
    • 495: 22 Exercise and Solution 02:15
    • 496: 23 Exercise and Solution Raw 02:22
    • 497: 23 Exercise and Solution 01:44
    • 498: 24 Exercise and Solution Raw 08:50
    • 499: 24 Exercise and Solution 03:48
    • 500: 25 Exercise and Solution Raw 02:58
    • 501: 25 Exercise and Solution 01:09
    • 502: 26 Log of Base 10 and e Raw 07:03
    • 503: 26 Log of Base 10 and e 02:55

    • 504: !Importance of Matrix 01:26
    • 505: !Importance of MatrixFINAL 00:40
    • 506: 1_Introduction_matrix 14:29
    • 507: 1_Introduction_matrixFINAL 07:19
    • 508: 2_Addition & Subtraction 02:56
    • 509: 2_Addition & SubtractionFINAL 01:13
    • 510: 3_Matrices Multiplication 13:02
    • 511: 3_Matrices MultiplicationFINAL 06:37
    • 512: 4_Square of Matrix 01:21
    • 513: 4_Square of MatrixFINAL 00:59
    • 514: 5_Transpose 03:53
    • 515: 5_TransposeFINAL 02:14
    • 516: 6_Special Matrix 07:18
    • 517: 6_Special MatrixFINAL 05:10
    • 518: 7_Determinant of a Matrix 04:13
    • 519: 7_Determinant of a MatrixFINAL 02:45
    • 520: 8_Determinant of a MatrixSingular Matrix 02:08
    • 521: 8_Determinant of a MatrixSingular MatrixFINAL 00:59
    • 522: 9-Cofactor 09:12
    • 523: 9-CofactorFINAL 04:28
    • 524: 10_Matrix of the Cofactors of the elements of a matrix 07:25
    • 525: 10_Matrix of the Cofactors of the elements of a matrixFINAL 03:40
    • 526: 11_Adjoint of a Squared Matrix 05:52
    • 527: 11_Adjoint of a Squared MatrixFINAL 03:03
    • 528: 12_Inverse of the a square matrix 09:56
    • 529: 12_Inverse of the a square matrixFINAL 04:40
    • 530: 12b_Inverse of Matrix 2X2 shorter 02:01
    • 531: 12b_Inverse of Matrix 2X2 shorterFINAL 01:53
    • 532: 13_Product of Matrix and its Inverse 04:40
    • 533: 13_Product of Matrix and its InverseFINAL 02:13
    • 534: 14_Matrix_Exercise & Solution 01:44
    • 535: 14_Matrix_Exercise & SolutionFINAL 00:49
    • 536: 15_Matrix_Exercise & Solution 02:54
    • 537: 15_Matrix_Exercise & SolutionFINAL 01:17
    • 538: 16_Matrix_Exercise & Solution 04:12
    • 539: 16_Matrix_Exercise & SolutionFINAL 01:44
    • 540: 17_Matrix_Exercise & Solution 02:22
    • 541: 17_Matrix_Exercise & SolutionFINAL 00:55
    • 542: 18_Matrix_Exercise & Solution 01:28
    • 543: 18_Matrix_Exercise & SolutionFINAL 01:08
    • 544: 19_Matrix_Exercise & Solution 01:41
    • 545: 19_Matrix_Exercise & SolutionFINAL 01:01
    • 546: 20_Matrix_Exercise & Solution 02:48
    • 547: 20_Matrix_Exercise & SolutionFINAL 01:04
    • 548: 21_Matrix_Exercise & Solution 01:08
    • 549: 21_Matrix_Exercise & SolutionFINAl 00:45
    • 550: 22_Matrix_Exercise & Solution 04:10
    • 551: 22_Matrix_Exercise & SolutionFINAL 01:26
    • 552: 23-Matrix for Simultaneous Equation 05:52
    • 553: 23-Matrix for Simultaneous EquationFINAL 03:00
    • 554: 24_COFactor Ex 13:01
    • 555: 24_COFactor ExFINAL 03:07
    • 556: 25_Cramer's Rule 08:11
    • 557: 25_Cramer's RuleFINAL 04:24
    • 558: 26_Cramer's RuleEx 08:36
    • 559: 26_Cramer's RuleExFINAL 03:32

    • 560: 1_Introduction 11:50
    • 561: 1_IntroductionFINAL 05:28
    • 562: Example 1 04:56
    • 563: Example 1FINAL 01:39
    • 564: Example 2 04:07
    • 565: Example 2FINAL 01:37
    • 566: Example 3 11:28
    • 567: Example 3FINAL 03:30
    • 568: Example 4 11:36
    • 569: Example 4FINAL 03:54

    • 570: 1_Gradient of a straight line 12:26
    • 571: 1_Gradient of a straight lineFINAL 05:10
    • 572: 2_Example Gradient 02:08
    • 573: 2_Example GradientFINAL 00:57
    • 574: 2_Example Gradientlittle 00:42
    • 575: 3_Gradient of a curve to understand differentiation 19:18
    • 576: 3_Gradient of a curve to understand differentiationFINAL 08:56

    • 577: 1_Derived defination form of first principle 05:34
    • 578: 1_Derived defination form of first principleFINAL 02:16
    • 579: 2_Examples 23:55
    • 580: 2_ExamplesFINAL 07:18
    • 581: 3_General Formula 01:25
    • 582: 3_General FormulaFINAL 01:04
    • 583: 4_Example 03:17
    • 584: 4_ExampleFINAL 01:11
    • 585: 5_Example 01:37
    • 586: 5_ExampleFINAL 01:03
    • 587: 6_Example 01:37
    • 588: 6_ExampleFINAL 00:50
    • 589: 7_Example 04:44
    • 590: 7_ExampleFINAL 02:25
    • 591: 8_Example 00:36
    • 592: 8_ExampleFINAL 00:20
    • 593: 9_Example 01:53
    • 594: 9_ExampleFINAL 00:54
    • 595: 10_Example 00:45
    • 596: 10_ExampleFINAL 00:22

    • 597: Second Derivative 02:31
    • 598: Second DerivativeFINAL 01:25

    • 599: Special Derivative Result 02:36
    • 600: Special Derivative ResultFINAL 01:12

    • 601: 1_Understanding Chain Rule 10:31
    • 602: 1_Understanding Chain RuleFINAL 04:36
    • 603: Example 1 03:13
    • 604: Example 1FINAL 01:40
    • 605: Example 2 03:17
    • 606: Example 2FINAL 01:32
    • 607: Example 3 02:21
    • 608: Example 3FINAL 01:22
    • 609: Example 4 01:30
    • 610: Example 4FINAL 00:57

    • 611: Understanding Product Rule 00:46
    • 612: Question and Solution 1 01:17
    • 613: Question and Solution 2 00:38
    • 614: Question and Solution 3 01:08
    • 615: Question and Solution 4 01:05
    • 616: Question and Solution 5 01:15
    • 617: Question and Solution 6 00:56
    • 618: Question and Solution 7 00:53

    • 619: Understanding Quotient 02:15
    • 620: Question and Solution 1 01:47
    • 621: Question and Solution 2 01:34

    • 622: Introduction 00:47

    • 623: 2_ExampleFINAL 04:48
    • 624: 3_Must KnowFINAL 01:18
    • 625: 4_Question and SolutionFINAL 00:53
    • 626: 5_Question and SolutionFINAL 00:40
    • 627: 6_Question and SolutionFINAL 01:02
    • 628: 7_Question and SolutionFINAL 00:49
    • 629: 8_Question and SolutionFINAL 00:28

    • 630: Question and Solution 1 01:51
    • 631: Question and Solution 2 01:18
    • 632: Question and Solution 3 01:36

    • 633: Example & Solution 1FINAL 03:15
    • 634: Example & Solution 2FINAL 01:03
    • 635: Example & Solution 3FINAL 01:03

    • 636: Example 01:19
    • 637: General Pattern 00:34
    • 638: Question and Solution 1 00:49
    • 639: Question and Solution 2 00:43
    • 640: Question and Solution 3 00:49

    • 641: Importance of Area Under Curve 00:50
    • 642: Understanding Area Under Curve 03:06
    • 643: Question and Solution 1 10:02
    • 644: Question and Solution 2 06:47
    • 645: Question and Solution 3 03:35

Course media

Description

Broadly speaking, Machine Learning refers to the automated identification of patterns in data. As such it has been a fertile ground for new statistical and algorithmic developments. The purpose of this course is to provide a mathematically rigorous introduction to these developments with emphasis on methods and their analysis.

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, calculus, optimization, probability, statistics, and many more are covered in this course.

If you want to excel in Machine or Deep Learning this course is highly recommended.

Who is this course for?

  • Those starting from scratch in Machine Learning

  • Those who wish to take their career to the next level

  • Professional in the field of Data Science

  • Professionals in the banking industry

  • Professionals in the insurance industry

Requirements

  • Basic maths

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Legal information

This course is advertised on reed.co.uk by the Course Provider, whose terms and conditions apply. Purchases are made directly from the Course Provider, and as such, content and materials are supplied by the Course Provider directly. Reed is acting as agent and not reseller in relation to this course. Reed's only responsibility is to facilitate your payment for the course. It is your responsibility to review and agree to the Course Provider's terms and conditions and satisfy yourself as to the suitability of the course you intend to purchase. Reed will not have any responsibility for the content of the course and/or associated materials.

FAQs

Study method describes the format in which the course will be delivered. At Reed Courses, courses are delivered in a number of ways, including online courses, where the course content can be accessed online remotely, and classroom courses, where courses are delivered in person at a classroom venue.

CPD stands for Continuing Professional Development. If you work in certain professions or for certain companies, your employer may require you to complete a number of CPD hours or points, per year. You can find a range of CPD courses on Reed Courses, many of which can be completed online.

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An endorsed course is a skills based course which has been checked over and approved by an independent awarding body. Endorsed courses are not regulated so do not result in a qualification - however, the student can usually purchase a certificate showing the awarding body's logo if they wish. Certain awarding bodies - such as Quality Licence Scheme and TQUK - have developed endorsement schemes as a way to help students select the best skills based courses for them.
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Similar subjects: Maths, Statistics, Data science
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