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download скачать Free download скачать : Machine Learning, Data Science and Generative AI with Python
mp4 | Video: h264,1280X720 | Audio: AAC, 44.1 KHz
Genre:eLearning | Language: English | Size:7.21 GB

Files Included :

001 Introduction.mp4 (59.57 MB)
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002 Udemy 101 Getting the Most From This Course.mp4 (17.4 MB)
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005 [Activity] WINDOWS Installing and Using Anaconda & Course Materials.mp4 (101.97 MB)
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006 [Activity] MAC Installing and Using Anaconda  & Course Materials.mp4 (96.18 MB)
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007 [Activity] LINUX Installing and Using Anaconda  & Course Materials.mp4 (85.52 MB)
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008 Python Basics, Part 1 [Optional].mp4 (26.9 MB)
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009 [Activity] Python Basics, Part 2 [Optional].mp4 (20.62 MB)
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010 [Activity] Python Basics, Part 3 [Optional].mp4 (5.14 MB)
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011 [Activity] Python Basics, Part 4 [Optional].mp4 (8.19 MB)
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012 Introducing the Pandas Library [Optional].mp4 (44.15 MB)
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001 Types of Data (Numerical, Categorical, Ordinal).mp4 (73.1 MB)
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002 Mean, Median, Mode.mp4 (15.96 MB)
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003 [Activity] Using mean, median, and mode in Python.mp4 (44.5 MB)
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004 [Activity] Variation and Standard Deviation.mp4 (103.39 MB)
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005 Probability Density Function; Probability Mass Function.mp4 (6.92 MB)
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006 Common Data Distributions (Normal, Binomial, Poisson, etc).mp4 (28.25 MB)
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007 [Activity] Percentiles and Moments.mp4 (42.56 MB)
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008 [Activity] A Crash Course in matplotlib.mp4 (78.7 MB)
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009 [Activity] Advanced Visualization with Seaborn.mp4 (96.14 MB)
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010 [Activity] Covariance and Correlation.mp4 (69.48 MB)
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011 [Exercise] Conditional Probability.mp4 (93.95 MB)
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012 Exercise Solution Conditional Probability of Purchase by Age.mp4 (15.01 MB)
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013 Bayes' Theorem.mp4 (56.12 MB)
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001 [Activity] Linear Regression.mp4 (92.96 MB)
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002 [Activity] Polynomial Regression.mp4 (60.55 MB)
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003 [Activity] Multiple Regression, and Predicting Car Prices.mp4 (94.14 MB)
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004 Multi-Level Models.mp4 (27.22 MB)
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001 Supervised vs  Unsupervised Learning, and TrainTest.mp4 (56.68 MB)
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002 [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.mp4 (21.62 MB)
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003 Bayesian Methods Concepts.mp4 (9.83 MB)
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004 [Activity] Implementing a Spam Classifier with  Naive Bayes.mp4 (81.39 MB)
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005 K-Means Clustering.mp4 (26.02 MB)
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006 [Activity] Clustering people based on income and age.mp4 (21.99 MB)
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007 Measuring Entropy.mp4 (12.14 MB)
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008 [Activity] WINDOWS Installing Graphviz.mp4 (949.28 KB)
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009 [Activity] MAC Installing Graphviz.mp4 (9.07 MB)
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010 [Activity] LINUX Installing Graphviz.mp4 (2.48 MB)
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011 Decision Trees Concepts.mp4 (81.5 MB)
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012 [Activity] Decision Trees Predicting Hiring Decisions.mp4 (57.79 MB)
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013 Ensemble Learning.mp4 (36.96 MB)
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014 [Activity] XGBoost.mp4 (79.28 MB)
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015 Support Vector Machines (SVM) Overview.mp4 (16.35 MB)
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016 [Activity] Using SVM to cluster people using scikit-learn.mp4 (38.49 MB)
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001 User-Based Collaborative Filtering.mp4 (81.69 MB)
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002 Item-Based Collaborative Filtering.mp4 (23.2 MB)
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003 [Activity] Finding Movie Similarities using Cosine Similarity.mp4 (82.67 MB)
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004 [Activity] Improving the Results of Movie Similarities.mp4 (56.06 MB)
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005 [Activity] Making Movie Recommendations with Item-Based Collaborative Filtering.mp4 (124.11 MB)
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006 [Exercise] Improve the recommender's results.mp4 (28 MB)
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001 K-Nearest-Neighbors Concepts.mp4 (14.04 MB)
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002 [Activity] Using KNN to predict a rating for a movie.mp4 (85.54 MB)
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003 Dimensionality Reduction; Principal Component Analysis (PCA).mp4 (38.13 MB)
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004 [Activity] PCA Example with the Iris data set.mp4 (65.77 MB)
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005 Data Warehousing Overview ETL and ELT.mp4 (58.71 MB)
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006 Reinforcement Learning.mp4 (125.18 MB)
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007 [Activity] Reinforcement Learning & Q-Learning with Gym.mp4 (62.79 MB)
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008 Understanding a Confusion Matrix.mp4 (7.38 MB)
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009 Measuring Classifiers (Precision, Recall, F1, ROC, AUC).mp4 (11.67 MB)
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001 BiasVariance Tradeoff.mp4 (23.63 MB)
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002 [Activity] K-Fold Cross-Validation to avoid overfitting.mp4 (56.9 MB)
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003 Data Cleaning and Normalization.mp4 (73.09 MB)
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004 [Activity] Cleaning web log data.mp4 (31.01 MB)
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005 Normalizing numerical data.mp4 (10.32 MB)
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006 [Activity] Detecting outliers.mp4 (27.15 MB)
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007 Feature Engineering and the Curse of Dimensionality.mp4 (14.56 MB)
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008 Imputation Techniques for Missing Data.mp4 (18.2 MB)
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009 Handling Unbalanced Data Oversampling, Undersampling, and SMOTE.mp4 (17.43 MB)
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010 Binning, Transforming, Encoding,  Scaling, and Shuffling.mp4 (42.72 MB)
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003 [Activity] Installing Spark.mp4 (141.36 MB)
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004 Spark Introduction.mp4 (24.96 MB)
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005 Spark and the Resilient Distributed Dataset (RDD).mp4 (22.3 MB)
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006 Introducing MLLib.mp4 (14.65 MB)
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007 Introduction to Decision Trees in Spark.mp4 (133.95 MB)
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008 [Activity] K-Means Clustering in Spark.mp4 (116.14 MB)
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009 TF  IDF.mp4 (65.66 MB)
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010 [Activity] Searching Wikipedia with Spark.mp4 (84.01 MB)
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011 [Activity] Using the Spark DataFrame API for MLLib.mp4 (65.11 MB)
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001 Deploying Models to Real-Time Systems.mp4 (17.22 MB)
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002 AB Testing Concepts.mp4 (32.02 MB)
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003 T-Tests and P-Values.mp4 (14.08 MB)
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004 [Activity] Hands-on With T-Tests.mp4 (47.77 MB)
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005 Determining How Long to Run an Experiment.mp4 (9.75 MB)
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006 AB Test Gotchas.mp4 (91.73 MB)
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001 Deep Learning Pre-Requisites.mp4 (70.4 MB)
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002 The History of Artificial Neural Networks.mp4 (68.87 MB)
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003 [Activity] Deep Learning in the Tensorflow Playground.mp4 (55.69 MB)
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004 Deep Learning Details.mp4 (30.9 MB)
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005 Introducing Tensorflow.mp4 (46.63 MB)
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006 [Activity] Using Tensorflow, Part 1.mp4 (107.7 MB)
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007 [Activity] Using Tensorflow, Part 2.mp4 (95.13 MB)
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008 [Activity] Introducing Keras.mp4 (72.03 MB)
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009 [Activity] Using Keras to Predict Political Affiliations.mp4 (88.85 MB)
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010 Convolutional Neural Networks (CNN's).mp4 (58.73 MB)
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011 [Activity] Using CNN's for handwriting recognition.mp4 (52.82 MB)
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012 Recurrent Neural Networks (RNN's).mp4 (32.81 MB)
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013 [Activity] Using a RNN for sentiment analysis.mp4 (73.55 MB)
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014 [Activity] Transfer Learning.mp4 (111.05 MB)
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015 Tuning Neural Networks Learning Rate and Batch Size Hyperparameters.mp4 (8.5 MB)
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016 Deep Learning Regularization with Dropout and Early Stopping.mp4 (19.84 MB)
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017 The Ethics of Deep Learning.mp4 (120.5 MB)
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001 Variational Auto-Encoders (VAE's) - how they work.mp4 (42.88 MB)
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002 Variational Auto-Encoders (VAE) - Hands-on with Fashion MNIST.mp4 (148.84 MB)
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003 Generative Adversarial Networks (GAN's) - How they work.mp4 (15.24 MB)
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004 Generative Adversarial Networks (GAN's) - Playing with some demos.mp4 (86.14 MB)
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005 Generative Adversarial Networks (GAN's) - Hands-on with Fashion MNIST.mp4 (126.11 MB)
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006 Learning More about Deep Learning.mp4 (20.21 MB)
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001 The Transformer Architecture (encoders, decoders, and self-attention ).mp4 (44.2 MB)
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002 Self-Attention, Masked Self-Attention, and Multi-Headed Self Attention in depth.mp4 (41.5 MB)
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003 Applications of Transformers (GPT).mp4 (20.19 MB)
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004 How GPT Works, Part 1 The GPT Transformer Architecture.mp4 (30.27 MB)
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005 How GPT Works, Part 2 Tokenization, Positional Encoding, Embedding.mp4 (28.55 MB)
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006 Fine Tuning  Transfer Learning with Transformers.mp4 (11.52 MB)
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007 [Activity] Tokenization with Google CoLab and HuggingFace.mp4 (78.96 MB)
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008 [Activity] Positional Encoding.mp4 (15.97 MB)
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009 [Activity] Masked, Multi-Headed Self Attention with BERT, BERTViz, and exBERT.mp4 (39.78 MB)
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010 [Activity] Using small and large GPT models within Google CoLab and HuggingFace.mp4 (69.34 MB)
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011 [Activity] Fine Tuning GPT with the IMDb dataset.mp4 (85.2 MB)
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012 From GPT to ChatGPT Deep Reinforcement Learning, Proximal Policy Gradients.mp4 (51.12 MB)
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013 From GPT to ChatGPT Reinforcement Learning from Human Feedback and Moderation.mp4 (37.75 MB)
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001 [Activity] The OpenAI Chat Completions API.mp4 (70.44 MB)
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002 [Activity] Using Tools and Functions in the OpenAI Chat Completion API.mp4 (61.23 MB)
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003 [Activity] The Images (DALL-E) API in OpenAI.mp4 (29.59 MB)
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004 [Activity] The Embeddings API in OpenAI Finding similarities between words.mp4 (32.93 MB)
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005 The Legacy Fine-Tuning API for GPT Models in OpenAI.mp4 (29.42 MB)
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006 [Demo] Fine-Tuning OpenAI's Davinci Model to simulate Data from Star Trek.mp4 (170.75 MB)
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007 The New OpenAI Fine-Tuning API; Fine-Tuning GPT-3 5 to simulate Commander Data!.mp4 (318.98 MB)
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008 [Activity] The OpenAI Moderation API.mp4 (17.15 MB)
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009 [Activity] The OpenAI Audio API (speech to text).mp4 (28.72 MB)
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001 Retrieval Augmented Generation (RAG) How it works, with some examples.mp4 (92.89 MB)
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002 Demo Using Retrieval Augmented Generation (RAG) to simulate Data from Star Trek.mp4 (184.47 MB)
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001 Your final project assignment Mammogram Classification.mp4 (51.6 MB)
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002 Final project review.mp4 (64.49 MB)
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001 More to Explore.mp4 (33.99 MB)
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Код:
 https://fikper.com/roDZV9qfJV/Machine.Learning.Data.Science.and.Generative.AI.with.Python.z01.html
https://fikper.com/M4A2vliFsY/Machine.Learning.Data.Science.and.Generative.AI.with.Python.z02.html
https://fikper.com/gy8Qpkx4eu/Machine.Learning.Data.Science.and.Generative.AI.with.Python.z03.html
https://fikper.com/fwiZ24BqC5/Machine.Learning.Data.Science.and.Generative.AI.with.Python.z04.html
https://fikper.com/SUvKkUGZeP/Machine.Learning.Data.Science.and.Generative.AI.with.Python.zip.html
Код:
 https://rapidgator.net/file/9418fb4b391d1191bfc0e67c989ba2bf/Machine.Learning.Data.Science.and.Generative.AI.with.Python.z01
https://rapidgator.net/file/e22730b735a95f04f8b679e008570560/Machine.Learning.Data.Science.and.Generative.AI.with.Python.z02
https://rapidgator.net/file/39e8bd3f6106dcd1f932a067ad04a1e1/Machine.Learning.Data.Science.and.Generative.AI.with.Python.z03
https://rapidgator.net/file/9dcc58578b0e48a0de01044f4c4e3467/Machine.Learning.Data.Science.and.Generative.AI.with.Python.z04
https://rapidgator.net/file/526ed5bc9eb3d37716d5557c160d1d88/Machine.Learning.Data.Science.and.Generative.AI.with.Python.zip

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