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Course content
Sections:
1
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Activities:
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Resources:
134
- 001-Introduction-J9nS-gitir
- 002-The Learning Diagram-ZDs3-gitir
- 003-Python-yazR-gitir
- 004-Supervised Learnimg-564O-gitir
- 005-Unsupervised Learning-yqCh-gitir
- 006-Reinforcement Learning-c7Ww-gitir
- 007-When to Use and Not to Use ML-AmNh-gitir
- 008-How to chose ML Algorithms-vhlc-gitir
- 009-Preeliminar Analysis-pLFM-gitir
- 010-The Target Variable-kEGt-gitir
- 011-Missing Data-Mk9a-gitir
- 012-Log Transformation Homocedasticity-1lF2-gitir
- 013-Outliers and Anomaly Detection-MOOa-gitir
- 014-Data Transformation-Vu24-gitir
- 015-Data Transformation cont-3ceH-gitir
- 016-Significant Differences-l4QP-gitir
- 017-Descriptive and Inferential Statistics-b20U-gitir
- 018-Variables and Metrics-gd38-gitir
- 019-Correlation and Covariance-ufq9-gitir
- 020-Uncertainity-IGaE-gitir
- 021-Frquentist versus Bayesian Probabilities-OLpD-gitir
- 022-Random Variables and Sampling-h179-gitir
- 023-Sampling Spaces-WDc2-gitir
- 024-Basic Definitions of Probabilities-beTI-gitir
- 025-Axions Theorems Independence-X45f-gitir
- 026-Conditional Probability-tgTz-gitir
- 027-Bayes Theorem and Naive Bayes Algorithm-X922-gitir
- 028-Expectation Chance and Likelihood-IYWb-gitir
- 029-Maximum Likelihood Estimation MLE-Zb1v-gitir
- 030-Simulations-fLGn-gitir
- 031-Monte Carlo Simulation Markov Chainn-Eeq9-gitir
- 032-Probability Distributions-ovSl-gitir
- 033-Families of Distributions-KQqF-gitir
- 034-Normal Distribution-hyvB-gitir
- 035-Tests for Normality-2Ru0-gitir
- 036-Exponential Distribution-2Urc-gitir
- 037-Weibull Distribution and Survival Analysis-npAo-gitir
- 038-Binomial Distribution-B0JT-gitir
- 039-Poisson Distribution-JUca-gitir
- 040-Hypothesis Testing-aWdR-gitir
- 041-The p value-6QIv-gitir
- 042-Critical Value Significance Confidence CLT LLN-9Fk2-gitir
- 043-Z and T Tests-KREv-gitir
- 044-Degrees of Freedom and F statistics-7UrJ-gitir
- 045-ANOVA-Rqa1-gitir
- 046-Chi Squared Test-0vZS-gitir
- 047-Statistical Power-GIAe-gitir
- 048-Robustness and Statistical Sufficiency-pxs6-gitir
- 049-Times Series Decommposition-Uhrx-gitir
- 050-Autoregressive Models-gssg-gitir
- 051-Arima-VQbQ-gitir
- 052-Linear and Non Linear Models-jkU1-gitir
- 053-Introduction to Linear Algebra-Wr1j-gitir
- 054-Types of Matrices-FSLO-gitir
- 055-Matrices Operations-pAY4-gitir
- 056-Linear Transformations-Hm98-gitir
- 057-Matrix Decomposition and Tensors-UKHj-gitir
- 058-Functions-RWBW-gitir
- 059-Limits-2QpQ-gitir
- 060-The Derivative-ffUl-gitir
- 061-Calculating the Derivative-2HJv-gitir
- 062-Maximum and Minimum-xf1e-gitir
- 063-Analitical vs Numerical Solutions-enNx-gitir
- 064-Numerical and Analytic Solution-fLxX-gitir
- 065-Gradient Descent-1spC-gitir
- 066-Distance Measurements-qMsQ-gitir
- 067-Similarities-2Juf-gitir
- 068-Knn and K means-xuVS-gitir
- 069-Distances in Python-JXRE-gitir
- 070-Training Testin Validation-YFRr-gitir
- 071-Training Testing Validation cont-jJjb-gitir
- 072-The Cost Function-hTRi-gitir
- 073-Cost Function for Regression and Classification-KUGX-gitir
- 074-Minimazing the Cost Function with Gradient Descent-GcPv-gitir
- 075-Batch annd Stochastic Gradient Descent-I6gt-gitir
- 076-Bias and Variance Introduction-Lxlj-gitir
- 077-Complexity-a7kA-gitir
- 078-Regularization-fnaW-gitir
- 079-Regularization Cont-A88v-gitir
- 080-Parametric and Non Parametric Algorithms-EqSf-gitir
- 081-Learning Curves-03rG-gitir
- 082-Learning Curves in Python-3Va5-gitir
- 083-PCA and SCD-Aauf-gitir
- 084-Eigenvectors and Eigenvalues-r9i8-gitir
- 085-Dimensionality Reduction in Python-ldjf-gitir
- 086-Entropy and Information Gain-JpV5-gitir
- 087-Entropy and Information Gain cont-WcqA-gitir
- 088-Linear Regression-1N6u-gitir
- 089-Linear Regression cont-TGXf-gitir
- 090-Polinomial Regression-zmb4-gitir
- 091-Logistic Function-yS5c-gitir
- 092-Generalized Linear Models GLM-yYtE-gitir
- 093-Decision Boundaries-SvU2-gitir
- 094-Confusion Matrix-LK9G-gitir
- 095-ROC and AUC-yhnM-gitir
- 096-Visualization of Class Distribution-Sngk-gitir
- 097-Precision and Recall-DGwA-gitir
- 098-Introduction to Decision Trees-49BK-gitir
- 099-Gini Index-VN6L-gitir
- 100-Hyperparameters-aXr2-gitir
- 101-Decision Trees in Python-OCTM-gitir
- 102-Introduction to SVMs-T1P6-gitir
- 103-Introduction to SVMs cont-ezrz-gitir
- 104-Mathematics of SVMs-LX2b-gitir
- 105-SVM in Python-N3EY-gitir
- 106-Wisdom of the Crowds-hoKG-gitir
- 107-Bagging and Random Forest-IYLf-gitir
- 108-Adaboost Gradient Boosting XGBoosting-z3ux-gitir
- 109-Introduction to NLP-4Eq7-gitir
- 110-Tokenization and Embeddings-DCWP-gitir
- 111-Weights and Representation-1pRT-gitir
- 112-Sequences and Sentiment Analysis-RSxX-gitir
- 113-Mathematical Model of Artificial Neuron-UNyY-gitir
- 114-Activation Functions-exrl-gitir
- 115-Activation Functions cont-CxLE-gitir
- 116-Weights and Bias Parameters-Zufm-gitir
- 117-Feedforward and Backpropagation Concepts-2yPM-gitir
- 118-Feedforward Process-zZsi-gitir
- 119-Backpropagation Process-0zqT-gitir
- 120-Recurent Neural Networks RNN-lImB-gitir
- 121-Convolution Neural Networks CNN-bYVB-gitir
- 122-Convolution Neural Networks CNN cont-yS5y-gitir
- 123-Seq2Seq and Aplications of NN-1CZI-gitir
- 124-Generative vs Descriptive AI-6Qt7-gitir
- 125-LLMs Properties-lR7Z-gitir
- 126-Introduction to Transformers-AOk0-gitir
- 127-Training and Inference-GXOJ-gitir
- 128-Basic Arquitecture of Transformers-VMGU-gitir
- 129-Encoder Workflow-rvVL-gitir
- 130-Sel Attention-gEV2-gitir
- 131-Multi Head Attention-3SpV-gitir
- 132-Normalization and Residual Connections-4586-gitir
- 133-Decoder-yVRC-gitir
- 134-Types of Transformers Arquitecture-ccyr-gitir