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2025 Data Science & AI Masters From Python To Gen AI ~ Udemy - Satyajit Pattnaik

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2025 Data Science & AI Masters From Python To Gen AI ~ Udemy - Satyajit Pattnaik

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Files:

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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