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FreeCourseSite com Udemy Machine Learning Hands On Python In Data Science

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[FreeCourseSite.com] Udemy - Machine Learning A-Z™ Hands-On Python & R In Data Science

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Total Size

7.2 GB

Total Files

287

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3D667B5BF82D1742616109A174A4B69253DA090A

/01 Welcome to the course/

001 Applications of Machine Learning.mp4

10.3 MB

002 Why Machine Learning is the Future.mp4

15.2 MB

003 Installing R and R Studio MAC Windows.mp4

24.3 MB

004 Installing Python and Anaconda MAC Windows.mp4

25.1 MB

005 BONUS Meet your instructors.html

1.4 KB

/02 -------------------------- Part 1 Data Preprocessing --------------------------/

006 Welcome to Part 1 - Data Preprocessing.mp4

3.7 MB

007 Get the dataset.mp4

22.2 MB

008 Importing the Libraries.mp4

14.2 MB

009 Importing the Dataset.mp4

30.0 MB

011 Missing Data.mp4

41.2 MB

012 Categorical Data.mp4

55.4 MB

013 Splitting the Dataset into the Training set and Test set.mp4

53.4 MB

014 Feature Scaling.mp4

46.8 MB

015 And here is our Data Preprocessing Template.mp4

27.1 MB

/quizzes/

001 Data Preprocessing.html

4.7 KB

/03 ------------------------------ Part 2 Regression ------------------------------/

016 Welcome to Part 2 - Regression.html

1.2 KB

/04 Simple Linear Regression/

017 How to get the dataset.mp4

12.3 MB

018 Dataset Business Problem Description.mp4

8.1 MB

019 Simple Linear Regression Intuition - Step 1.mp4

11.0 MB

020 Simple Linear Regression Intuition - Step 2.mp4

6.3 MB

021 Simple Linear Regression in Python - Step 1.mp4

29.3 MB

022 Simple Linear Regression in Python - Step 2.mp4

25.8 MB

023 Simple Linear Regression in Python - Step 3.mp4

21.5 MB

024 Simple Linear Regression in Python - Step 4.mp4

41.3 MB

025 Simple Linear Regression in R - Step 1.mp4

12.1 MB

026 Simple Linear Regression in R - Step 2.mp4

26.1 MB

027 Simple Linear Regression in R - Step 3.mp4

12.0 MB

028 Simple Linear Regression in R - Step 4.mp4

51.5 MB

/quizzes/

002 Simple Linear Regression.html

4.6 KB

/05 Multiple Linear Regression/

029 How to get the dataset.mp4

12.3 MB

030 Dataset Business Problem Description.mp4

13.2 MB

031 Multiple Linear Regression Intuition - Step 1.mp4

2.1 MB

032 Multiple Linear Regression Intuition - Step 2.mp4

2.1 MB

033 Multiple Linear Regression Intuition - Step 3.mp4

17.4 MB

034 Multiple Linear Regression Intuition - Step 4.mp4

5.6 MB

035 Multiple Linear Regression Intuition - Step 5.mp4

34.4 MB

036 Multiple Linear Regression in Python - Step 1.mp4

54.7 MB

037 Multiple Linear Regression in Python - Step 2.mp4

10.3 MB

038 Multiple Linear Regression in Python - Step 3.mp4

26.7 MB

039 Multiple Linear Regression in Python - Backward Elimination - Preparation.mp4

57.2 MB

040 Multiple Linear Regression in Python - Backward Elimination - HOMEWORK.mp4

62.0 MB

041 Multiple Linear Regression in Python - Backward Elimination - Homework Solution.mp4

56.9 MB

042 Multiple Linear Regression in R - Step 1.mp4

24.6 MB

043 Multiple Linear Regression in R - Step 2.mp4

47.4 MB

044 Multiple Linear Regression in R - Step 3.mp4

14.5 MB

045 Multiple Linear Regression in R - Backward Elimination - HOMEWORK.mp4

53.3 MB

046 Multiple Linear Regression in R - Backward Elimination - Homework Solution.mp4

23.0 MB

/quizzes/

003 Multiple Linear Regression.html

4.8 KB

/06 Polynomial Regression/

047 Polynomial Regression Intuition.mp4

9.9 MB

048 How to get the dataset.mp4

12.3 MB

049 Polynomial Regression in Python - Step 1.mp4

33.2 MB

050 Polynomial Regression in Python - Step 2.mp4

36.8 MB

051 Polynomial Regression in Python - Step 3.mp4

57.1 MB

052 Polynomial Regression in Python - Step 4.mp4

18.5 MB

053 Python Regression Template.mp4

38.6 MB

054 Polynomial Regression in R - Step 1.mp4

22.2 MB

055 Polynomial Regression in R - Step 2.mp4

33.9 MB

056 Polynomial Regression in R - Step 3.mp4

57.5 MB

057 Polynomial Regression in R - Step 4.mp4

29.9 MB

058 R Regression Template.mp4

32.9 MB

/07 Support Vector Regression SVR/

059 How to get the dataset.mp4

12.3 MB

060 SVR in Python.mp4

63.1 MB

061 SVR in R.mp4

35.4 MB

/08 Decision Tree Regression/

062 Decision Tree Regression Intuition.mp4

26.6 MB

063 How to get the dataset.mp4

12.3 MB

064 Decision Tree Regression in Python.mp4

45.5 MB

065 Decision Tree Regression in R.mp4

59.0 MB

/09 Random Forest Regression/

066 Random Forest Regression Intuition.mp4

16.4 MB

067 How to get the dataset.mp4

12.3 MB

068 Random Forest Regression in Python.mp4

55.3 MB

069 Random Forest Regression in R.mp4

54.4 MB

/10 Evaluating Regression Models Performance/

070 R-Squared Intuition.mp4

10.3 MB

071 Adjusted R-Squared Intuition.mp4

22.5 MB

072 Evaluating Regression Models Performance - Homeworks Final Part.mp4

29.7 MB

073 Interpreting Linear Regression Coefficients.mp4

28.7 MB

074 Conclusion of Part 2 - Regression.html

3.4 KB

/11 ---------------------------- Part 3 Classification ----------------------------/

075 Welcome to Part 3 - Classification.html

1.1 KB

/12 Logistic Regression/

076 Logistic Regression Intuition.mp4

30.6 MB

077 How to get the dataset.mp4

12.3 MB

078 Logistic Regression in Python - Step 1.mp4

17.7 MB

079 Logistic Regression in Python - Step 2.mp4

11.6 MB

080 Logistic Regression in Python - Step 3.mp4

8.4 MB

081 Logistic Regression in Python - Step 4.mp4

14.5 MB

082 Logistic Regression in Python - Step 5.mp4

55.7 MB

083 Python Classification Template.mp4

18.4 MB

084 Logistic Regression in R - Step 1.mp4

16.5 MB

085 Logistic Regression in R - Step 2.mp4

15.6 MB

086 Logistic Regression in R - Step 3.mp4

28.8 MB

087 Logistic Regression in R - Step 4.mp4

12.3 MB

088 Logistic Regression in R - Step 5.mp4

98.3 MB

089 R Classification Template.mp4

18.4 MB

/quizzes/

004 Logistic Regression.html

4.2 KB

/13 K-Nearest Neighbors K-NN/

090 K-Nearest Neighbor Intuition.mp4

11.0 MB

091 How to get the dataset.mp4

12.3 MB

092 K-NN in Python.mp4

49.3 MB

093 K-NN in R.mp4

58.5 MB

/quizzes/

005 K-Nearest Neighbor.html

4.2 KB

/14 Support Vector Machine SVM/

094 SVM Intuition.mp4

20.9 MB

095 How to get the dataset.mp4

12.3 MB

096 SVM in Python.mp4

43.7 MB

097 SVM in R.mp4

68.5 MB

/.../097 SVM in R/

SVM.zip

8.5 KB

/15 Kernel SVM/

098 Kernel SVM Intuition.mp4

6.7 MB

099 Mapping to a higher dimension.mp4

16.1 MB

100 The Kernel Trick.mp4

36.4 MB

101 Types of Kernel Functions.mp4

16.5 MB

102 How to get the dataset.mp4

12.3 MB

103 Kernel SVM in Python.mp4

57.5 MB

104 Kernel SVM in R.mp4

55.4 MB

/16 Naive Bayes/

105 Bayes Theorem.mp4

52.9 MB

106 Naive Bayes Intuition.mp4

32.6 MB

107 Naive Bayes Intuition Challenge Reveal.mp4

13.9 MB

108 Naive Bayes Intuition Extras.mp4

19.9 MB

109 How to get the dataset.mp4

12.3 MB

110 Naive Bayes in Python.mp4

32.7 MB

111 Naive Bayes in R.mp4

52.2 MB

/17 Decision Tree Classification/

112 Decision Tree Classification Intuition.mp4

22.7 MB

113 How to get the dataset.mp4

12.3 MB

114 Decision Tree Classification in Python.mp4

40.7 MB

115 Decision Tree Classification in R.mp4

71.5 MB

/18 Random Forest Classification/

116 Random Forest Classification Intuition.mp4

26.9 MB

117 How to get the dataset.mp4

12.3 MB

118 Random Forest Classification in Python.mp4

65.1 MB

119 Random Forest Classification in R.mp4

67.2 MB

/19 Evaluating Classification Models Performance/

120 False Positives False Negatives.mp4

15.9 MB

121 Confusion Matrix.mp4

9.3 MB

122 Accuracy Paradox.mp4

4.4 MB

123 CAP Curve.mp4

21.3 MB

124 CAP Curve Analysis.mp4

13.6 MB

125 Conclusion of Part 3 - Classification.html

4.0 KB

/20 ---------------------------- Part 4 Clustering ----------------------------/

126 Welcome to Part 4 - Clustering.html

1.0 KB

/21 K-Means Clustering/

127 K-Means Clustering Intuition.mp4

31.4 MB

128 K-Means Random Initialization Trap.mp4

16.1 MB

129 K-Means Selecting The Number Of Clusters.mp4

26.9 MB

130 How to get the dataset.mp4

12.3 MB

131 K-Means Clustering in Python.mp4

52.2 MB

132 K-Means Clustering in R.mp4

38.7 MB

/quizzes/

006 K-Means Clustering.html

4.2 KB

/22 Hierarchical Clustering/

133 Hierarchical Clustering Intuition.mp4

17.3 MB

134 Hierarchical Clustering How Dendrograms Work.mp4

18.3 MB

135 Hierarchical Clustering Using Dendrograms.mp4

23.9 MB

136 How to get the dataset.mp4

12.3 MB

137 HC in Python - Step 1.mp4

14.4 MB

138 HC in Python - Step 2.mp4

16.3 MB

139 HC in Python - Step 3.mp4

17.0 MB

140 HC in Python - Step 4.mp4

22.4 MB

141 HC in Python - Step 5.mp4

10.4 MB

142 HC in R - Step 1.mp4

9.0 MB

143 HC in R - Step 2.mp4

14.5 MB

144 HC in R - Step 3.mp4

10.4 MB

145 HC in R - Step 4.mp4

10.7 MB

146 HC in R - Step 5.mp4

14.3 MB

147 Conclusion of Part 4 - Clustering.html

0.8 KB

/quizzes/

007 Hierarchical Clustering.html

4.5 KB

/23 ---------------------- Part 5 Association Rule Learning ----------------------/

148 Welcome to Part 5 - Association Rule Learning.html

0.7 KB

/24 Apriori/

149 Apriori Intuition.mp4

36.7 MB

150 How to get the dataset.mp4

12.3 MB

151 Apriori in R - Step 1.mp4

55.4 MB

152 Apriori in R - Step 2.mp4

40.7 MB

153 Apriori in R - Step 3.mp4

59.3 MB

154 Apriori in Python - Step 1.mp4

49.7 MB

155 Apriori in Python - Step 2.mp4

39.1 MB

156 Apriori in Python - Step 3.mp4

37.0 MB

/25 Eclat/

157 Eclat Intuition.mp4

11.2 MB

158 How to get the dataset.mp4

12.3 MB

159 Eclat in R.mp4

26.5 MB

/.../159 Eclat in R/

Eclat.zip

49.7 KB

/26 ------------------------ Part 6 Reinforcement Learning ------------------------/

160 Welcome to Part 6 - Reinforcement Learning.html

1.1 KB

/27 Upper Confidence Bound UCB/

161 The Multi-Armed Bandit Problem.mp4

31.7 MB

162 Upper Confidence Bound UCB Intuition.mp4

30.7 MB

163 How to get the dataset.mp4

12.3 MB

164 Upper Confidence Bound in Python - Step 1.mp4

40.9 MB

165 Upper Confidence Bound in Python - Step 2.mp4

46.7 MB

166 Upper Confidence Bound in Python - Step 3.mp4

56.3 MB

167 Upper Confidence Bound in Python - Step 4.mp4

13.0 MB

168 Upper Confidence Bound in R - Step 1.mp4

35.7 MB

169 Upper Confidence Bound in R - Step 2.mp4

35.8 MB

170 Upper Confidence Bound in R - Step 3.mp4

60.6 MB

171 Upper Confidence Bound in R - Step 4.mp4

10.0 MB

/28 Thompson Sampling/

172 Thompson Sampling Intuition.mp4

39.1 MB

173 Algorithm Comparison UCB vs Thompson Sampling.mp4

14.8 MB

174 How to get the dataset.mp4

12.3 MB

175 Thompson Sampling in Python - Step 1.mp4

58.2 MB

176 Thompson Sampling in Python - Step 2.mp4

11.8 MB

177 Thompson Sampling in R - Step 1.mp4

53.5 MB

178 Thompson Sampling in R - Step 2.mp4

10.0 MB

/29 --------------------- Part 7 Natural Language Processing ---------------------/

179 Welcome to Part 7 - Natural Language Processing.html

2.0 KB

180 How to get the dataset.mp4

12.3 MB

181 Natural Language Processing in Python - Step 1.mp4

48.3 MB

182 Natural Language Processing in Python - Step 2.mp4

28.8 MB

183 Natural Language Processing in Python - Step 3.mp4

4.4 MB

184 Natural Language Processing in Python - Step 4.mp4

31.2 MB

185 Natural Language Processing in Python - Step 5.mp4

19.7 MB

186 Natural Language Processing in Python - Step 6.mp4

8.7 MB

187 Natural Language Processing in Python - Step 7.mp4

23.2 MB

188 Natural Language Processing in Python - Step 8.mp4

54.5 MB

189 Natural Language Processing in Python - Step 9.mp4

19.8 MB

190 Natural Language Processing in Python - Step 10.mp4

34.5 MB

191 Homework Challenge.html

1.7 KB

192 Natural Language Processing in R - Step 1.mp4

53.7 MB

193 Natural Language Processing in R - Step 2.mp4

22.7 MB

194 Natural Language Processing in R - Step 3.mp4

17.7 MB

195 Natural Language Processing in R - Step 4.mp4

8.6 MB

196 Natural Language Processing in R - Step 5.mp4

6.1 MB

197 Natural Language Processing in R - Step 6.mp4

16.9 MB

198 Natural Language Processing in R - Step 7.mp4

10.1 MB

199 Natural Language Processing in R - Step 8.mp4

18.1 MB

200 Natural Language Processing in R - Step 9.mp4

39.5 MB

201 Natural Language Processing in R - Step 10.mp4

56.8 MB

202 Homework Challenge.html

1.7 KB

/30 ---------------------------- Part 8 Deep Learning ----------------------------/

203 Welcome to Part 8 - Deep Learning.html

1.2 KB

204 What is Deep Learning.mp4

32.8 MB

/31 Artificial Neural Networks/

205 Plan of attack.mp4

5.0 MB

206 The Neuron.mp4

31.3 MB

207 The Activation Function.mp4

15.5 MB

208 How do Neural Networks work.mp4

24.7 MB

209 How do Neural Networks learn.mp4

27.8 MB

210 Gradient Descent.mp4

19.4 MB

211 Stochastic Gradient Descent.mp4

17.6 MB

212 Backpropagation.mp4

11.5 MB

213 How to get the dataset.mp4

12.3 MB

214 Business Problem Description.mp4

30.7 MB

215 ANN in Python - Step 1 - Installing Theano Tensorflow and Keras.mp4

39.3 MB

216 ANN in Python - Step 2.mp4

89.0 MB

217 ANN in Python - Step 3.mp4

15.3 MB

218 ANN in Python - Step 4.mp4

10.2 MB

219 ANN in Python - Step 5.mp4

41.3 MB

220 ANN in Python - Step 6.mp4

12.5 MB

221 ANN in Python - Step 7.mp4

15.6 MB

222 ANN in Python - Step 8.mp4

35.7 MB

223 ANN in Python - Step 9.mp4

29.9 MB

224 ANN in Python - Step 10.mp4

29.8 MB

225 ANN in R - Step 1.mp4

52.3 MB

226 ANN in R - Step 2.mp4

19.1 MB

227 ANN in R - Step 3.mp4

39.7 MB

228 ANN in R - Step 4 Last step.mp4

45.9 MB

/32 Convolutional Neural Networks/

229 Plan of attack.mp4

6.2 MB

230 What are convolutional neural networks.mp4

30.9 MB

231 Step 1 - Convolution Operation.mp4

32.5 MB

232 Step 1b - ReLU Layer.mp4

14.8 MB

233 Step 2 - Pooling.mp4

42.2 MB

234 Step 3 - Flattening.mp4

3.4 MB

235 Step 4 - Full Connection.mp4

44.8 MB

236 Summary.mp4

8.3 MB

237 Softmax Cross-Entropy.mp4

34.8 MB

238 How to get the dataset.mp4

12.3 MB

239 CNN in Python - Step 1.mp4

32.1 MB

240 CNN in Python - Step 2.mp4

7.6 MB

241 CNN in Python - Step 3.mp4

2.9 MB

242 CNN in Python - Step 4.mp4

36.3 MB

243 CNN in Python - Step 5.mp4

13.0 MB

244 CNN in Python - Step 6.mp4

12.5 MB

245 CNN in Python - Step 7.mp4

17.5 MB

246 CNN in Python - Step 8.mp4

9.4 MB

247 CNN in Python - Step 9.mp4

65.4 MB

248 CNN in Python - Step 10.mp4

29.1 MB

249 CNN in R.html

2.7 KB

/33 ----------------------- Part 9 Dimensionality Reduction -----------------------/

250 Welcome to Part 9 - Dimensionality Reduction.html

1.6 KB

/34 Principal Component Analysis PCA/

251 How to get the dataset.mp4

12.3 MB

252 PCA in Python - Step 1.mp4

33.5 MB

253 PCA in Python - Step 2.mp4

23.1 MB

254 PCA in Python - Step 3.mp4

26.7 MB

255 PCA in R - Step 1.mp4

32.1 MB

256 PCA in R - Step 2.mp4

30.4 MB

257 PCA in R - Step 3.mp4

38.5 MB

/35 Linear Discriminant Analysis LDA/

258 How to get the dataset.mp4

12.3 MB

259 LDA in Python.mp4

47.6 MB

260 LDA in R.mp4

53.8 MB

/36 Kernel PCA/

261 How to get the dataset.mp4

12.3 MB

262 Kernel PCA in Python.mp4

35.0 MB

263 Kernel PCA in R.mp4

59.3 MB

/37 --------------------- Part 10 Model Selection Boosting ---------------------/

264 Welcome to Part 10 - Model Selection Boosting.html

1.2 KB

/38 Model Selection/

265 How to get the dataset.mp4

12.3 MB

266 k-Fold Cross Validation in Python.mp4

34.4 MB

267 k-Fold Cross Validation in R.mp4

45.8 MB

268 Grid Search in Python - Step 1.mp4

40.1 MB

269 Grid Search in Python - Step 2.mp4

30.9 MB

270 Grid Search in R.mp4

37.3 MB

/39 XGBoost/

271 How to get the dataset.mp4

12.3 MB

272 XGBoost in Python - Step 1.mp4

22.4 MB

273 XGBoost in Python - Step 2.mp4

33.5 MB

274 XGBoost in R.mp4

49.6 MB

/40 Bonus Lectures/

275 YOUR SPECIAL BONUS.html

5.1 KB

/

[FreeCourseSite.com].txt

1.1 KB

[FreeCourseSite.com].url

0.1 KB

[HaxTech.me].txt

1.1 KB

[HaxTech.me].url

0.1 KB

 

Total files 287


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