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Language:
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Total Size:
46.6 GB
Info Hash:
FD698251C71C7F3BDCC4F663A851565957F7DCDF
Added By:
Added:
Oct. 6, 2025, 3:03 a.m.
Stats:
|
(Last updated: Nov. 13, 2025, 1:28 a.m.)
| File | Size |
|---|---|
| 02. - Python+Installation+Guide.pdf | 842.0 KB |
| 10 - Power+BI+Ebook.pdf | 14.4 MB |
| 10 - RAG+with+GrokAI.ipynb | 20.0 KB |
| 10 - RAG+with+Ollama.ipynb | 10.0 KB |
| 10 - RAGPaper (1).pdf | 864.6 KB |
| 10 - RAGPaper.pdf | 864.6 KB |
| 1 Welcome Page.mp4 | 51.5 MB |
| 10 Datatypes Operators.mp4 | 364.2 MB |
| 11 Lists.mp4 | 465.6 MB |
| 12 Tuples.mp4 | 424.2 MB |
| 13 Sets.mp4 | 220.6 MB |
| 14 Dictionary.mp4 | 297.3 MB |
| 15 Loops & Iterations.mp4 | 336.2 MB |
| 16 Functions.mp4 | 393.9 MB |
| 17 Map Reduce Filter.mp4 | 514.8 MB |
| 18 File Handling.mp4 | 327.3 MB |
| 19 Control Structures.mp4 | 171.9 MB |
| 20 OOPs.mp4 | 335.2 MB |
| 21 NumPy.mp4 | 485.4 MB |
| 22 Pandas.mp4 | 567.4 MB |
| 23 Data Visualization.mp4 | 113.4 MB |
| 24 Matplotlib.mp4 | 449.7 MB |
| 25 Seaborn.mp4 | 325.2 MB |
| 5 Let's install Python together!!.mp4 | 273.2 MB |
| 6 Google Colab, what's that.mp4 | 51.4 MB |
| 7 Let's leverage chatGPT for help!!.mp4 | 70.8 MB |
| 8 Introduction to Python.mp4 | 94.2 MB |
| 9 Variables & Keywords.mp4 | 352.3 MB |
| 27 Introduction.mp4 | 42.3 MB |
| 28 Types of Data (Agenda).mp4 | 3.2 MB |
| 29 Descriptive Stats.mp4 | 79.8 MB |
| 30 Inferential Stats.mp4 | 13.4 MB |
| 31 Qualitative Data.mp4 | 50.0 MB |
| 32 Quantitative Data.mp4 | 20.5 MB |
| 33 Sampling Techniques (Agenda).mp4 | 7.6 MB |
| 34 Population vs Sample.mp4 | 17.9 MB |
| 35 Why Sampling is important.mp4 | 17.0 MB |
| 36 Types of Sampling.mp4 | 20.7 MB |
| 37 Cluster Random Sampling.mp4 | 30.6 MB |
| 38 Probability Sampling.mp4 | 40.7 MB |
| 39 Non probability sampling.mp4 | 31.4 MB |
| 40 Population Sampling.mp4 | 56.4 MB |
| 41 Why n-1 and not n.mp4 | 32.8 MB |
| 42 Descriptive Analytics (Agenda).mp4 | 5.0 MB |
| 43 Measures of Central Tendency.mp4 | 9.1 MB |
| 44 Mean.mp4 | 27.0 MB |
| 45 Median.mp4 | 36.5 MB |
| 46 Mode.mp4 | 28.1 MB |
| 47 Measures of Dispersion.mp4 | 21.6 MB |
| 48 Range.mp4 | 7.3 MB |
| 49 IQR.mp4 | 19.5 MB |
| 50 Variance Standard Deviation.mp4 | 56.4 MB |
| 51 Mean Deviation.mp4 | 18.9 MB |
| 52 Probability (Agenda).mp4 | 4.7 MB |
| 53 Probability.mp4 | 42.0 MB |
| 54 Addition Rule.mp4 | 45.4 MB |
| 55 Independent Events.mp4 | 26.0 MB |
| 56 Cumulative Probability.mp4 | 29.4 MB |
| 57 Conditional Probability.mp4 | 57.9 MB |
| 58 Bayes Theorem 1.mp4 | 9.5 MB |
| 59 Bayes Theorem 2.mp4 | 25.0 MB |
| 60 Probability Distrubution (Agenda).mp4 | 10.4 MB |
| 61 Uniform Distribution.mp4 | 44.1 MB |
| 62 Binomial Distribution.mp4 | 70.8 MB |
| 63 Poisson Distribution.mp4 | 18.8 MB |
| 64 Normal Distribution Part 1.mp4 | 77.5 MB |
| 65 Normal Distribution Part 2.mp4 | 34.3 MB |
| 66 Skewness.mp4 | 25.2 MB |
| 67 Kurtosis.mp4 | 14.1 MB |
| 68 Calc Prob w Z-score - Normal Distrib Pt 1.mp4 | 49.6 MB |
| 69 Calc Prob w Z-score - Normal Distrib Pt 2.mp4 | 47.0 MB |
| 70 Calc Prob w Z-score - Normal Distrib Pt 3.mp4 | 27.0 MB |
| 71 Covariance & Correlation (Agenda).mp4 | 2.7 MB |
| 72 Covariance.mp4 | 54.4 MB |
| 73 Correlation.mp4 | 86.6 MB |
| 74 Covariance VS Correlation.mp4 | 26.6 MB |
| 75 Hypothesis Testing.mp4 | 52.9 MB |
| 76 Tailed Tests.mp4 | 16.8 MB |
| 77 p-value.mp4 | 32.0 MB |
| 78 Types of Test.mp4 | 26.9 MB |
| 79 T Test.mp4 | 51.3 MB |
| 80 Z Test.mp4 | 67.4 MB |
| 81 Chi Square Test.mp4 | 67.3 MB |
| 82 ANOVA.mp4 | 68.9 MB |
| 83 Correlation Test (Practicals).mp4 | 44.6 MB |
| 100 Types of Data.mp4 | 11.0 MB |
| 101 Types of Analysis.mp4 | 12.0 MB |
| 102 Univariate Analysis.mp4 | 54.1 MB |
| 103 Bivariate Analysis.mp4 | 35.7 MB |
| 104 Multivariate Analysis.mp4 | 5.2 MB |
| 105 Numerical Analysis.mp4 | 19.4 MB |
| 106 Analysis Practicals.mp4 | 211.5 MB |
| 107 Derived Metrics.mp4 | 26.5 MB |
| 108 Feature Binning (Theory).mp4 | 44.2 MB |
| 109 Feature Binning (Practicals).mp4 | 71.0 MB |
| 110 Feature Encoding (Theory).mp4 | 83.8 MB |
| 111 Feature Encoding (Practicals).mp4 | 169.8 MB |
| 112 Case Study.mp4 | 79.6 MB |
| 113 Data Exploration.mp4 | 151.4 MB |
| 114 Data Cleaning.mp4 | 73.5 MB |
| 115 Univariate Analysis.mp4 | 97.6 MB |
| 116 Bivariate Analysis Part 1.mp4 | 129.3 MB |
| 117 Bivariate Analysis Part 2.mp4 | 54.5 MB |
| 118 EDA Report.mp4 | 35.8 MB |
| 85 Agenda.mp4 | 15.2 MB |
| 86 DA,DS Processes.mp4 | 24.3 MB |
| 87 What is EDA.mp4 | 27.1 MB |
| 88 Visualization.mp4 | 30.5 MB |
| 89 Steps involved in EDA (Data Sourcing).mp4 | 28.8 MB |
| 90 Steps involved in EDA (Data Cleaning).mp4 | 30.4 MB |
| 91 Handle Missing Values (Theory).mp4 | 58.5 MB |
| 92 Handle Missing Values (Practicals).mp4 | 92.1 MB |
| 93 Feature Scaling (Theory).mp4 | 74.2 MB |
| 94 Standardization Example.mp4 | 22.7 MB |
| 95 Normalization Example.mp4 | 13.9 MB |
| 96 Feature Scaling (Practicals).mp4 | 111.6 MB |
| 97 Outlier Treatment (Theory).mp4 | 59.8 MB |
| 98 Outlier Treatment (Practicals).mp4 | 102.7 MB |
| 99 Invalid Data.mp4 | 42.5 MB |
| 120 Installation.mp4 | 59.1 MB |
| 121 Data Architect - File server vs client server.mp4 | 119.3 MB |
| 122 Introduction to SQL.mp4 | 164.5 MB |
| 123 Constraints in SQL.mp4 | 289.4 MB |
| 124 Table Basics - DDLs.mp4 | 396.5 MB |
| 125 Table Basics - DQLs.mp4 | 290.0 MB |
| 126 Table Basics - DMLs.mp4 | 461.6 MB |
| 127 Joins.mp4 | 448.4 MB |
| 128 Data Import Export.mp4 | 545.6 MB |
| 129 Aggregation Functions.mp4 | 211.2 MB |
| 130 String functions.mp4 | 287.9 MB |
| 131 Date Time Functions.mp4 | 233.9 MB |
| 132 Regular Expressions.mp4 | 160.7 MB |
| 133 Nested Queries.mp4 | 263.5 MB |
| 134 Views.mp4 | 222.8 MB |
| 135 Stored Procedures.mp4 | 439.1 MB |
| 136 Windows Function.mp4 | 365.8 MB |
| 137 SQL Python connectivity.mp4 | 341.3 MB |
| 138 Agenda.mp4 | 13.7 MB |
| 139 Introduction to ML.mp4 | 32.2 MB |
| 140 Types of ML.mp4 | 104.9 MB |
| 141 Use Cases Part 1.mp4 | 19.9 MB |
| 142 Use Cases Part 2.mp4 | 8.0 MB |
| 143 Pre-Requisites Features.mp4 | 88.7 MB |
| 144 Pre-Requisites Train-Test Split.mp4 | 115.8 MB |
| 145 Pre-Requisites Feature Scaling.mp4 | 74.2 MB |
| 146 Pre-Requisites Standardization Example.mp4 | 22.7 MB |
| 147 Pre-Requisites Normalization Example.mp4 | 13.9 MB |
| 148 Pre-Requisites Feature Encoding.mp4 | 83.8 MB |
| 149 Pre-Req Feature Encoding (Practicals).mp4 | 78.8 MB |
| 150 Regression Intro to Regression Models.mp4 | 38.9 MB |
| 151 Regression Regression Metrics.mp4 | 151.4 MB |
| 152 Regression Regression Metrics (Practicals).mp4 | 102.6 MB |
| 153 Regression Simple Linear Regression.mp4 | 55.9 MB |
| 154 Regression Multiple Linear Regression.mp4 | 51.5 MB |
| 155 Regression Linear Regression (Practicals).mp4 | 210.8 MB |
| 156 Regress Multi Linear Regress (Practicals).mp4 | 96.2 MB |
| 157 Regression Polynomial Regression.mp4 | 39.2 MB |
| 158 Regression Polynomial Regress (Practicals).mp4 | 176.6 MB |
| 159 Regression Bias Variance Tradeoff.mp4 | 31.0 MB |
| 160 Regression Ridge Regression.mp4 | 55.2 MB |
| 161 Regression Lasso Regression.mp4 | 43.9 MB |
| 162 Regress Lasso, Ridge Regress (Practicals).mp4 | 335.4 MB |
| 163 Classification Intro to Classification.mp4 | 41.3 MB |
| 164 Classification Types of Classification.mp4 | 25.7 MB |
| 165 Classification Log Loss.mp4 | 63.6 MB |
| 166 Classification Confusion Matrix.mp4 | 72.8 MB |
| 167 Classification AUC ROC Curve.mp4 | 48.6 MB |
| 168 Classification Classification Report.mp4 | 47.2 MB |
| 169 Classification kNN Classifier.mp4 | 80.8 MB |
| 170 Classification kNN Classifier Example.mp4 | 78.0 MB |
| 171 Classification Practicals Part 1.mp4 | 100.5 MB |
| 172 Classification kNN Classifier (Practicals).mp4 | 115.4 MB |
| 173 Classification Decision Tree.mp4 | 73.0 MB |
| 174 Class.. Decision Tree (Entropy based).mp4 | 112.5 MB |
| 175 Classification Decision Tree (gini based).mp4 | 104.2 MB |
| 176 Classification Decision Tree (Practicals).mp4 | 66.5 MB |
| 177 Classification Decision Tree (Visualizing).mp4 | 160.3 MB |
| 178 Classification Random Forest Classifier.mp4 | 40.9 MB |
| 179 Class.. Random Forest Classifier (Practs).mp4 | 46.7 MB |
| 180 Classification Naive Bayes Classifier.mp4 | 89.9 MB |
| 181 Classification SVM Classifier Part 1.mp4 | 71.8 MB |
| 182 Classification SVM Classifier Part 2.mp4 | 60.2 MB |
| 183 Classification Logistic Regression.mp4 | 119.2 MB |
| 184 Classification Practicals so far.mp4 | 218.7 MB |
| 185 Class.. Issues in Classification (Part 1).mp4 | 48.4 MB |
| 186 Class.. Issues in Classification (Part 2).mp4 | 80.2 MB |
| 187 Classification Project.mp4 | 308.9 MB |
| 188 Ensemble Intro to Ensemble Learning.mp4 | 117.9 MB |
| 189 Ensemble Bagging.mp4 | 50.6 MB |
| 190 Ensemble Bagging vs Random Forest.mp4 | 91.1 MB |
| 191 Ensemble Bagging (Practicals #1).mp4 | 241.2 MB |
| 192 Ensemble Bagging (Practicals #2).mp4 | 178.1 MB |
| 193 Ensemble Boosting.mp4 | 41.9 MB |
| 194 Ensemble Ada Boost.mp4 | 97.9 MB |
| 195 Ensemble Gradient Boost.mp4 | 20.8 MB |
| 196 Ensemble CF vs LF.mp4 | 47.1 MB |
| 197 Ensemble Cross Entropy.mp4 | 22.1 MB |
| 198 Ensemble Xtreme Gradient Boosting (XGB).mp4 | 94.4 MB |
| 199 Ensemble Project.mp4 | 210.6 MB |
| 200 Clustering Introduction to Clustering.mp4 | 104.0 MB |
| 201 Clustering kMeans Clustering.mp4 | 121.0 MB |
| 202 Clustering kMeans Clustering (Practicals).mp4 | 133.4 MB |
| 203 Clustering Hierarchical Clustering.mp4 | 81.9 MB |
| 204 Clustering Hierarchy Cluster (Practicals).mp4 | 106.5 MB |
| 205 Clustering Mean Shift Clustering.mp4 | 73.3 MB |
| 206 Feature Engineering Introduction.mp4 | 87.4 MB |
| 207 Feature Engineering RFE and SFS.mp4 | 29.0 MB |
| 208 Feature Engineering RFE (Practicals).mp4 | 190.9 MB |
| 209 Feature Eng.. Successive Feature Selection.mp4 | 180.1 MB |
| 210 Feature Engineering Chi-Square.mp4 | 31.7 MB |
| 211 Feature Eng.. Chi-Square (Practicals).mp4 | 54.6 MB |
| 212 Feat Eng Principal Component Analysis.mp4 | 258.2 MB |
| 213 Feat Eng Principal Component Analy (Practls).mp4 | 79.7 MB |
| 214 Feat Eng Linear Discriminant Analysis.mp4 | 54.2 MB |
| 215 Feat Eng Linear Discriminant Analysis (Practls).mp4 | 84.9 MB |
| 216 Feature Engineering kPCA & QDA.mp4 | 53.5 MB |
| 217 Feature Engineering kPCA & QDA (Practicals).mp4 | 50.7 MB |
| 218 Hyper Parameter Optimization (HPO) Basics.mp4 | 76.0 MB |
| 219 Hyper Parameter Optimization Manual HPO.mp4 | 31.9 MB |
| 220 HPO GridSearch vs RandomizedSearch.mp4 | 70.8 MB |
| 221 HPO Manual HPO (Practicals).mp4 | 164.8 MB |
| 222 HPO RandomizedSearchCV (Practicals).mp4 | 138.8 MB |
| 223 HPO GridSearchCV (Practicals).mp4 | 60.4 MB |
| 224 Introduction to TSA.mp4 | 23.3 MB |
| 225 Time Series vs Regression.mp4 | 77.1 MB |
| 226 Time Series Analysis.mp4 | 14.6 MB |
| 227 Anomaly Detection.mp4 | 29.9 MB |
| 228 Components of Time Series.mp4 | 46.3 MB |
| 229 Decomposition.mp4 | 6.5 MB |
| 230 Decomposition (Practicals).mp4 | 46.5 MB |
| 231 AdditiveMultiplicative Decomp.mp4 | 38.9 MB |
| 232 Stationarity.mp4 | 28.5 MB |
| 233 Testing TS Stationarity.mp4 | 43.6 MB |
| 234 Transformation.mp4 | 21.4 MB |
| 235 Introduction to Pre-Processing.mp4 | 17.8 MB |
| 236 Handle Missing Value.mp4 | 58.5 MB |
| 237 Handle Missing Value (Practicals).mp4 | 92.1 MB |
| 238 Outlier Treatment.mp4 | 59.8 MB |
| 239 3-Sigma Technique.mp4 | 102.7 MB |
| 240 Feature Scaling.mp4 | 74.2 MB |
| 241 Feature Scaling Standardization.mp4 | 22.7 MB |
| 242 Feature Scaling Normalization.mp4 | 14.0 MB |
| 243 Feature Scaling (Practicals).mp4 | 111.6 MB |
| 244 Feature Encoding.mp4 | 83.8 MB |
| 245 Feature Encoding (Practicals).mp4 | 78.8 MB |
| 246 Models - Algorithms.mp4 | 5.8 MB |
| 247 Models - ARIMA Part 1.mp4 | 11.4 MB |
| 248 Models - ARIMA Part 2.mp4 | 32.1 MB |
| 249 Models - AR Theory.mp4 | 41.7 MB |
| 250 Models - MA Theory.mp4 | 46.0 MB |
| 251 Models - ACFPACF Plots.mp4 | 45.4 MB |
| 252 Models - Find p,d,q in ARIMA.mp4 | 11.9 MB |
| 253 Models - ARIMA (Practicals Part 1).mp4 | 90.9 MB |
| 254 Models - ARIMA (Practicals Part 2).mp4 | 85.7 MB |
| 255 Models - ARIMA (Final).mp4 | 70.7 MB |
| 256 Models - Decomposition.mp4 | 31.8 MB |
| 257 Models - ACFPACF.mp4 | 21.6 MB |
| 258 Models - Best Transformation.mp4 | 72.3 MB |
| 259 Models - Grid Search (Part 1).mp4 | 90.1 MB |
| 260 Models - Grid Search (Part 2).mp4 | 16.9 MB |
| 261 Models - Final Model Building.mp4 | 83.6 MB |
| 262 Models - Facebook Prophet (Part 1).mp4 | 52.0 MB |
| 263 Models - Facebook Prophet (Part 2).mp4 | 84.7 MB |
| 264 Models - Facebook Prophet (Part 3).mp4 | 51.9 MB |
| 265 Mods - Multi Variate Time Series Analy.mp4 | 42.6 MB |
| 266 Mods - Facebook Prophet Uni v Multi.mp4 | 118.2 MB |
| 267 Introduction to Metrics.mp4 | 30.0 MB |
| 268 Forecasting Evaluation Metrics.mp4 | 6.7 MB |
| 269 Mean Squarred Error.mp4 | 7.0 MB |
| 270 Root Mean Squarred Error.mp4 | 7.1 MB |
| 271 Mean Absolute Percentage Error.mp4 | 16.3 MB |
| 272 Proj 1 - Energy Forecasting Part 1.mp4 | 25.6 MB |
| 273 Proj 1 - Energy Forecasting Part 2.mp4 | 53.2 MB |
| 274 Proj 1 - Energy Forecasting Part 3.mp4 | 77.7 MB |
| 275 Proj 2 - Stock Market Prediction Pt 1.mp4 | 30.6 MB |
| 276 Proj 2 - Stock Market Prediction Pt 2.mp4 | 37.7 MB |
| 277 Proj 2 - Stock Market Prediction Pt 3.mp4 | 152.5 MB |
| 278 Proj 3 - Demand Forecasting Part 1.mp4 | 24.1 MB |
| 279 Proj 3 - Demand Forecasting Part 2.mp4 | 113.4 MB |
| 280 Proj 3 - Demand Forecasting Part 3.mp4 | 94.1 MB |
| 281 Proj 3 - Demand Forecasting Part 4.mp4 | 10.8 MB |
| 282 Proj 3 - Demand Forecasting Part 5.mp4 | 141.1 MB |
| 283 Proj 3 - Demand Forecasting Part 6.mp4 | 79.8 MB |
| 285 Introduction to Deep Learning.mp4 | 10.6 MB |
| 286 Understanding Deep Learning.mp4 | 92.8 MB |
| 287 What is a Neuron.mp4 | 132.7 MB |
| 288 Activation Functions.mp4 | 70.4 MB |
| 289 Activation Function Step Function.mp4 | 91.4 MB |
| 290 Activation Function Linear Function.mp4 | 171.0 MB |
| 291 Activation Function Sigmoid Function.mp4 | 93.5 MB |
| 292 Activation Function TanH Function.mp4 | 45.9 MB |
| 293 Activation Function ReLu Function.mp4 | 148.4 MB |
| 294 Backpropagation & Forward Pass.mp4 | 212.4 MB |
| 295 Gradient Descent.mp4 | 107.4 MB |
| 296 Artificial Neural Networks Intuition.mp4 | 28.2 MB |
| 297 Artificial Neural Networks Practicals.mp4 | 140.8 MB |
| 298 Artificial NN Hyper Param Optimize.mp4 | 101.9 MB |
| 299 Convolutional Neural Networks (CNN).mp4 | 123.1 MB |
| 300 CNN Steps in CNN.mp4 | 176.2 MB |
| 301 CNN Architecture Explained.mp4 | 253.1 MB |
| 302 CNN Image Augmentation.mp4 | 205.7 MB |
| 303 CNN Batch size vs iterations vs epochs.mp4 | 120.9 MB |
| 304 CNN Practicals.mp4 | 308.3 MB |
| 305 CNN Model Summary & Parameters.mp4 | 113.5 MB |
| 306 CNN Project (X-Ray detection).mp4 | 260.9 MB |
| 307 Recurrent Neural Networks (RNN) Basics.mp4 | 35.2 MB |
| 308 RNN Types of RNN.mp4 | 19.0 MB |
| 309 RNN Vanishing, Exploding Gradient Prob.mp4 | 94.6 MB |
| 310 RNN LSTMs.mp4 | 36.2 MB |
| 311 RNN LSTMs (Practicals).mp4 | 89.0 MB |
| 312 Pre-Trained Models.mp4 | 172.0 MB |
| 313 Pre-Trained Models (Practicals).mp4 | 214.2 MB |
| 314 Pre-Trained Models VGG16.mp4 | 75.9 MB |
| 315 Pre-Trained Models MobileNet.mp4 | 46.8 MB |
| 316 Transfer Learning.mp4 | 39.2 MB |
| 317 Proj Pneumonia Detection X-Ray Img.mp4 | 124.3 MB |
| 319 Intro to NLP Introduction.mp4 | 59.1 MB |
| 320 Intro to NLP Introduction continued.mp4 | 46.9 MB |
| 321 Intro to NLP Key Challenges.mp4 | 67.5 MB |
| 322 Intro to NLP Linguistics.mp4 | 31.1 MB |
| 323 NLP Basics Case Folding.mp4 | 28.0 MB |
| 324 NLP Basics SCR.mp4 | 89.8 MB |
| 325 NLP Basics Handling Contractions.mp4 | 64.6 MB |
| 326 NLP Basics Tokenization.mp4 | 38.9 MB |
| 327 NLP Basics Stop Word Removal.mp4 | 40.6 MB |
| 328 NLP Basics nGrams.mp4 | 52.3 MB |
| 329 NLP Basics Vectorization.mp4 | 24.4 MB |
| 330 NLP Basics Word Embeddings.mp4 | 14.5 MB |
| 331 NLP Basics Bag of Words.mp4 | 50.7 MB |
| 332 NLP Basics Bag of Words (Practicals).mp4 | 154.6 MB |
| 333 NLP Basics TF-IDF.mp4 | 68.6 MB |
| 334 NLP Basics TF-IDF (Practicals).mp4 | 150.4 MB |
| 335 NLP Part of Speech Tag, Named Entity Recog.mp4 | 57.3 MB |
| 336 NLP Basics NER (Practicals).mp4 | 96.9 MB |
| 337 Word Embeddings Word2Vec Introduction.mp4 | 23.7 MB |
| 338 Word Embeddings Word2Vec Part 2.mp4 | 13.6 MB |
| 339 Word Embeddings Pre-Trained Word2Vec.mp4 | 62.3 MB |
| 340 Word Embeddings Word2Vec Intuition.mp4 | 37.5 MB |
| 341 Word Embed Word2Vec - Check X Features.mp4 | 65.8 MB |
| 342 Word Embeddings Word2Vec CBOW.mp4 | 103.3 MB |
| 343 Word Embed Word2Vec Skip Grams.mp4 | 55.9 MB |
| 344 Word Embeddings GloVe.mp4 | 79.4 MB |
| 345 Word Embeddings FastText.mp4 | 142.0 MB |
| 346 Word Embeddings Cosine Similarity.mp4 | 95.0 MB |
| 347 Neural Networks (NN) LSTMs Part 1.mp4 | 73.4 MB |
| 348 NN LSTMs Part 2 (Architecture).mp4 | 107.0 MB |
| 349 NN LSTMs Part 3 (Deep Dive).mp4 | 28.3 MB |
| 350 NN LSTMs Part 4 Pointwise Operation.mp4 | 34.7 MB |
| 351 NN LSTMs Part 5 (forget gate).mp4 | 61.8 MB |
| 352 NN LSTMs Part 6 (inpute gate).mp4 | 115.0 MB |
| 353 NN LSTMs Part 7 (output gate).mp4 | 49.5 MB |
| 354 NN LSTMs Part 8 (Practicals #1).mp4 | 219.8 MB |
| 355 NN LSTMs Part 9 (Practicals #2).mp4 | 90.1 MB |
| 356 NN LSTMs Part 10 (Practicals #3).mp4 | 112.5 MB |
| 357 NN GRU Part 1.mp4 | 19.8 MB |
| 358 NN GRU Part 2.mp4 | 146.2 MB |
| 359 NN GRU Part 3 (reset gate).mp4 | 41.3 MB |
| 360 NN GRU Part 4 (update gate).mp4 | 44.6 MB |
| 361 NN GRU Part 5 (Practicals).mp4 | 105.5 MB |
| 362 NN Bi-Directional LSTMs.mp4 | 116.3 MB |
| 364 Transformer Types.mp4 | 127.4 MB |
| 365 Introduction to Transformers.mp4 | 145.8 MB |
| 366 Self Attention.mp4 | 125.4 MB |
| 367 Encoder Architecture.mp4 | 48.0 MB |
| 368 Contextual Embeddings.mp4 | 30.2 MB |
| 369 Decoder Architecture.mp4 | 31.4 MB |
| 370 Introduction to BERT.mp4 | 72.1 MB |
| 371 Configurations of BERT.mp4 | 25.4 MB |
| 372 BERT Fine Tuning.mp4 | 21.3 MB |
| 373 BERT Pre Tuning (Masked LM).mp4 | 50.1 MB |
| 374 BERT Input Embeddings.mp4 | 62.1 MB |
| 375 ARLM vs AELM.mp4 | 43.4 MB |
| 376 RoBERTa.mp4 | 60.4 MB |
| 377 DistilBERT.mp4 | 92.4 MB |
| 378 AlBERT.mp4 | 112.4 MB |
| 379 Introduction to GPT (Decoder Only).mp4 | 30.5 MB |
| 380 GPT Architecture.mp4 | 27.7 MB |
| 381 GPT Masked Multi Head Attention.mp4 | 86.0 MB |
| 382 GPT Blocks.mp4 | 48.9 MB |
| 383 GPT Training.mp4 | 54.6 MB |
| 385 LLM Basics Context Window.mp4 | 56.2 MB |
| 386 LLM Basics Prompt.mp4 | 63.9 MB |
| 387 LLM Basics Prompt Engineering.mp4 | 119.9 MB |
| 388 LLM Basics Prompt Tuning.mp4 | 57.1 MB |
| 389 LLM Basics Prompt Structures.mp4 | 106.9 MB |
| 390 RAGs Introduction to RAG.mp4 | 5.7 MB |
| 391 RAGs What and Why.mp4 | 119.2 MB |
| 392 RAGs Use Cases.mp4 | 138.8 MB |
| 393 RAGs Paper Explanation.mp4 | 53.3 MB |
| 394 RAGs Architecture Explanation.mp4 | 106.5 MB |
| 395 RAGs Detailed Architect Walk-thru.mp4 | 74.8 MB |
| 396 RAGs Practical Use Cases.mp4 | 256.5 MB |
| 397 LangChain.mp4 | 83.3 MB |
| 398 Intro Prompt Engineering.mp4 | 81.0 MB |
| 399 Types of Prompting.mp4 | 90.4 MB |
| 400 Few Shot Limitations.mp4 | 50.7 MB |
| 401 Chain of Thoughts Prompting.mp4 | 45.0 MB |
| 402 Vector Databases.mp4 | 86.4 MB |
| 403 Vector Database vs Vector Index.mp4 | 60.8 MB |
| 404 How Vector Databases works.mp4 | 72.1 MB |
| 405 Vector Database (Practicals).mp4 | 260.8 MB |
| 406 LSH.mp4 | 85.4 MB |
| 407 Model Overview Ollama.mp4 | 310.6 MB |
| 408 Getting Started Ollama.mp4 | 317.0 MB |
| 409 Model Testing Ollama.mp4 | 384.5 MB |
| 410 Python Implementation Ollama.mp4 | 131.6 MB |
| 411 RAG Systems Ollama.mp4 | 69.0 MB |
| 412 RAG Systems (Practicals) Ollama.mp4 | 219.3 MB |
| 413 Model Overview LLM APIs.mp4 | 198.6 MB |
| 414 RAG Systems with xAI LLM APIs.mp4 | 34.1 MB |
| 415 RAG Sys w xAI (Practicals) LLM APIs.mp4 | 141.5 MB |
| 416 Deployment Basics.mp4 | 27.4 MB |
| 417 Introduction to Flask.mp4 | 72.2 MB |
| 418 Flask Basic App.mp4 | 88.4 MB |
| 419 Model Building (Breast Cancer Predict).mp4 | 135.8 MB |
| 420 Flask App (Breast Cancer Prediction).mp4 | 187.8 MB |
| 421 AWS.mp4 | 58.9 MB |
| 422 AWS Deploy (Breast Cancer Predict).mp4 | 238.2 MB |
| 423 Introduction to Data Engineering.mp4 | 3.3 MB |
| 424 What is ETL.mp4 | 39.3 MB |
| 425 ETL Tools.mp4 | 25.1 MB |
| 426 What is Data Warehouse.mp4 | 26.6 MB |
| 427 Benefits of Data Warehouse.mp4 | 18.9 MB |
| 428 Data Warehouse Structure.mp4 | 19.1 MB |
| 429 Why do we need Staging.mp4 | 30.4 MB |
| 430 What are Data Marts.mp4 | 11.8 MB |
| 431 Data Lake.mp4 | 22.4 MB |
| 432 Data lake vs Data Warehouse.mp4 | 28.5 MB |
| 433 Elements of Datalake.mp4 | 14.6 MB |
| 434 ChatScholar (EdTech Project).mp4 | 399.7 MB |
| 435 Research RAG Chatbot.mp4 | 295.1 MB |
| 436 Auto AI Claims Processing - Gen AI.mp4 | 403.9 MB |
| 437 PDF RAG(s) Chatbot Web Scrape Data.mp4 | 309.7 MB |
| 438 AI Career Coach Part 1.mp4 | 94.0 MB |
| 439 AI Career Coach Part 2.mp4 | 112.5 MB |
| 440 AI Career Coach Part 3.mp4 | 223.2 MB |
| 441 Sustainability Chatbot (GROK AI).mp4 | 379.5 MB |
| 442 ML Interview Prep.mp4 | 49.2 MB |
| 443 ML Interview #1.mp4 | 178.0 MB |
| 444 ML Interview #2.mp4 | 205.0 MB |
| 445 ML Interview #3.mp4 | 145.7 MB |
| 446 ML Interview #4.mp4 | 143.2 MB |
| 447 ML Interview #5.mp4 | 98.4 MB |
| 448 ML Interview #6.mp4 | 151.3 MB |
| 449 ML Interview #7.mp4 | 117.3 MB |
| 450 ML Interview #8.mp4 | 137.4 MB |
| 451 ML Interview #9.mp4 | 182.6 MB |
| 452 ML Interview #10.mp4 | 136.4 MB |
| 453 DL Interview #1.mp4 | 162.6 MB |
| 454 DL Interview #2.mp4 | 110.6 MB |
| 455 DL Interview #3.mp4 | 94.5 MB |
| 456 DL Interview #4.mp4 | 102.5 MB |
| 457 DL Interview #5.mp4 | 118.7 MB |
| 458 DL Interview #6.mp4 | 148.4 MB |
| 459 DL Interview #7.mp4 | 55.1 MB |
| 460 DL Interview #8.mp4 | 140.0 MB |
| 461 DL Interview #9.mp4 | 58.6 MB |
| 462 DL Interview #10.mp4 | 136.6 MB |
| 463 Gen AI Interview #1.mp4 | 76.8 MB |
| 464 Gen AI Interview #2.mp4 | 90.5 MB |
| 465 Gen AI Interview #3.mp4 | 157.7 MB |
| 466 Gen AI Interview #4.mp4 | 126.8 MB |
| 467 Gen AI Interview #5.mp4 | 122.9 MB |
| 468 Gen AI Interview #6.mp4 | 144.1 MB |
| 469 Gen AI Interview #7.mp4 | 116.4 MB |
| 470 Gen AI Interview #8.mp4 | 150.2 MB |
| 471 Gen AI Interview #9.mp4 | 149.2 MB |
| 472 Gen AI Interview #10.mp4 | 156.0 MB |
| 473 Gen AI Interview #2.mp4 | 90.5 MB |
| 474 Gen AI Interview #3.mp4 | 157.7 MB |
| 475 Gen AI Interview #4.mp4 | 126.8 MB |
| 476 Gen AI Interview #5.mp4 | 122.9 MB |
| 477 Gen AI Interview #6.mp4 | 144.1 MB |
| 478 Gen AI Interview #7.mp4 | 116.4 MB |
| 479 Gen AI Interview #8.mp4 | 150.2 MB |
| 480 Gen AI Interview #9.mp4 | 149.2 MB |
| 481 Gen AI Interview #10.mp4 | 156.0 MB |
| 2025 Data Science & AI Masters From Python To Gen AI ~ Udemy - Satyajit Pattnaiko.txt | 228 bytes |
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31.7 MB
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2023-07-01
| Uploaded by FreeCourseWeb | Size 2.8 MB | Health [ 17 /1 ] | Added 2023-07-01 |
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9.6 MB
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| Uploaded by FreeCourseWeb | Size 9.6 MB | Health [ 10 /2 ] | Added 2023-06-22 |
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NOTE
SOURCE: 2025 Data Science & AI Masters From Python To Gen AI ~ Udemy - Satyajit Pattnaik
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MEDIAINFO
. 2025 Data Science & AI Masters From Python To Gen AI ~ Udemy - Satyajit Pattnaik https://www.udemy.com/course/data-science-ai-masters-from-python-to-gen-ai === . Credit due: TorrentDay BOOKWARE-BOOKTIME id=8827293 ###
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