Cursos de Aprendizaje Profundo

4 horas

25 capítulos

Avanzado

7 ESTUDIANDO AHORA

Habilidades Adquiridas: Neural Networks, Model Training and Evaluation, Data Preprocessing, Hyperparameter Tuning, Machine Learning with scikit-learn

5 horas

29 capítulos

Avanzado

1 ESTUDIANDO AHORA

Habilidades Adquiridas: Natural Language Processing, Natural Language Handling

2 horas

16 capítulos

Intermedio

2 ESTUDIANDO AHORA

Habilidades Adquiridas: TensorFlow Basics, Neural Networks, Python Data Structures, Data Preprocessing

3 horas

22 capítulos

Intermedio

1 ESTUDIANDO AHORA

Habilidades Adquiridas: Understanding RNNs, LSTMs, and GRUs, Implementing recurrent networks in PyTorch, Processing time series and sequential data, Applying RNNs to NLP tasks (sentiment analysis) , End-to-end model development and evaluation

5 horas

51 capítulos

Principiante

14 ESTUDIANDO AHORA

Habilidades Adquiridas: Functions & Sets, Series Analysis , Limits & Derivatives , Integrals , Gradient Descent , Vectors & Matrices , Linear Transformations , Matrix Decomposition , Probability Rules , Bayes' Theorem, Statistical Measures , Probability Distributions

1 hora

9 capítulos

Principiante

1 ESTUDIANDO AHORA

Habilidades Adquiridas: Prompt Engineering Fundamentals , Role and Context Prompting , Few-Shot Prompting , Chain-of-Thought Prompting , Structured Output Design , Prompt Refinement , Prompt Evaluation

3 horas

20 capítulos

Avanzado

4 ESTUDIANDO AHORA

Habilidades Adquiridas: PyTorch Basics, Neural Networks, Model Training and Evaluation

4 horas

29 capítulos

Intermedio

2 ESTUDIANDO AHORA

Habilidades Adquiridas: Image Processing with OpenCV, Convolutional Neural Networks, Object Detection Approaches

2 horas

15 capítulos

Intermedio

Habilidades Adquiridas: Mathematical Foundations of Loss Functions, Risk Minimization Theory, Regression Loss Analysis, Classification Loss Analysis, Information-Theoretic Losses, Loss Function Selection and Comparison

1 hora

12 capítulos

Principiante

Habilidades Adquiridas: AI Ethics Fundamentals , Ethical Decision-Making , Fairness and Bias Analysis , Transparency Principles , Accountability in AI , Data Privacy Concepts , Responsible AI Frameworks , Regulatory Awareness

1 hora

12 capítulos

Principiante

3 ESTUDIANDO AHORA

Habilidades Adquiridas: Data Cleaning , Missing Value Imputation , Outlier Detection , Feature Encoding , Feature Scaling , Data Transformation , Feature Engineering , Feature Selection , Pipeline Building

1 hora

15 capítulos

Principiante

1 ESTUDIANDO AHORA

Habilidades Adquiridas: Explainable AI Fundamentals, XAI Methods and Concepts, Ethical AI Principles, AI Transparency Awareness