From 3cb05d321022481dc2c35acb0ed6c9a764358327 Mon Sep 17 00:00:00 2001 From: Arthur DANJOU Date: Sat, 13 Dec 2025 23:38:27 +0100 Subject: [PATCH] Update Python version in Jupyter notebooks to 3.13.9 across multiple files --- L3/Calculs Numériques/Interpolation.ipynb | 2 +- L3/Calculs Numériques/Methode_de_Newton.ipynb | 2 +- M1/Numerical Methods/TP2_DANJOU_Arthur.ipynb | 2 +- M1/Numerical Methods/TP_DANJOU_Arthur.ipynb | 2 +- M1/Numerical Optimisation/ComputerSession1.ipynb | 2 +- M1/Numerical Optimisation/ComputerSession3.ipynb | 2 +- M1/Statistical Learning/TP5_Naive_Bayes.ipynb | 2 +- M1/Statistical Learning/TP6_keras_intro.ipynb | 2 +- M1/Statistical Learning/neural_network.ipynb | 2 +- M2/Deep Learning/TP3 - Compléments/TP3 - Starter.ipynb | 2 +- M2/Deep Learning/TP4 - Récurrents/TP4 - Bonus.ipynb | 2 +- M2/Deep Learning/TP4 - Récurrents/TP4 - Starter.ipynb | 2 +- M2/Machine Learning/TP_1/2025_TP_1_M2_ISF.ipynb | 2 +- M2/Machine Learning/TP_2/2025_TP_2_M2_ISF.ipynb | 2 +- M2/Machine Learning/TP_3/2025_TP_3_M2_ISF.ipynb | 2 +- M2/Machine Learning/TP_4/2025_M2_ISF_TP_4.ipynb | 2 +- M2/Machine Learning/TP_5/2025_M2_ISF_TP_5.ipynb | 2 +- ...‘Armed Bandits with epsilon‑Greedy and Bernoulli Rewards.ipynb | 2 +- 18 files changed, 18 insertions(+), 18 deletions(-) diff --git a/L3/Calculs Numériques/Interpolation.ipynb b/L3/Calculs Numériques/Interpolation.ipynb index 6c5e224..cfa8c31 100644 --- a/L3/Calculs Numériques/Interpolation.ipynb +++ b/L3/Calculs Numériques/Interpolation.ipynb @@ -654,7 +654,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.3" + "version": "3.13.9" }, "toc": { "base_numbering": 1, diff --git a/L3/Calculs Numériques/Methode_de_Newton.ipynb b/L3/Calculs Numériques/Methode_de_Newton.ipynb index 432113c..b351415 100644 --- a/L3/Calculs Numériques/Methode_de_Newton.ipynb +++ b/L3/Calculs Numériques/Methode_de_Newton.ipynb @@ -995,7 +995,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.3" + "version": "3.13.9" } }, "nbformat": 4, diff --git a/M1/Numerical Methods/TP2_DANJOU_Arthur.ipynb b/M1/Numerical Methods/TP2_DANJOU_Arthur.ipynb index 7edc7b3..16479ec 100644 --- a/M1/Numerical Methods/TP2_DANJOU_Arthur.ipynb +++ b/M1/Numerical Methods/TP2_DANJOU_Arthur.ipynb @@ -509,7 +509,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.3" + "version": "3.13.9" } }, "nbformat": 4, diff --git a/M1/Numerical Methods/TP_DANJOU_Arthur.ipynb b/M1/Numerical Methods/TP_DANJOU_Arthur.ipynb index 17ed746..11cc4c5 100644 --- a/M1/Numerical Methods/TP_DANJOU_Arthur.ipynb +++ b/M1/Numerical Methods/TP_DANJOU_Arthur.ipynb @@ -412,7 +412,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.3" + "version": "3.13.9" } }, "nbformat": 4, diff --git a/M1/Numerical Optimisation/ComputerSession1.ipynb b/M1/Numerical Optimisation/ComputerSession1.ipynb index 5bfe864..f58fdaf 100644 --- a/M1/Numerical Optimisation/ComputerSession1.ipynb +++ b/M1/Numerical Optimisation/ComputerSession1.ipynb @@ -951,7 +951,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.3" + "version": "3.13.9" } }, "nbformat": 4, diff --git a/M1/Numerical Optimisation/ComputerSession3.ipynb b/M1/Numerical Optimisation/ComputerSession3.ipynb index 704ef34..08528a4 100644 --- a/M1/Numerical Optimisation/ComputerSession3.ipynb +++ b/M1/Numerical Optimisation/ComputerSession3.ipynb @@ -503,7 +503,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.3" + "version": "3.13.9" } }, "nbformat": 4, diff --git a/M1/Statistical Learning/TP5_Naive_Bayes.ipynb b/M1/Statistical Learning/TP5_Naive_Bayes.ipynb index 4fe75aa..ac003ce 100644 --- a/M1/Statistical Learning/TP5_Naive_Bayes.ipynb +++ b/M1/Statistical Learning/TP5_Naive_Bayes.ipynb @@ -2206,7 +2206,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.3" + "version": "3.13.9" } }, "nbformat": 4, diff --git a/M1/Statistical Learning/TP6_keras_intro.ipynb b/M1/Statistical Learning/TP6_keras_intro.ipynb index 8a5f916..ead31f9 100644 --- a/M1/Statistical Learning/TP6_keras_intro.ipynb +++ b/M1/Statistical Learning/TP6_keras_intro.ipynb @@ -2286,7 +2286,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.3" + "version": "3.13.9" } }, "nbformat": 4, diff --git a/M1/Statistical Learning/neural_network.ipynb b/M1/Statistical Learning/neural_network.ipynb index 1c830f4..010b9e6 100644 --- a/M1/Statistical Learning/neural_network.ipynb +++ b/M1/Statistical Learning/neural_network.ipynb @@ -545,7 +545,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.3" + "version": "3.13.9" } }, "nbformat": 4, diff --git a/M2/Deep Learning/TP3 - Compléments/TP3 - Starter.ipynb b/M2/Deep Learning/TP3 - Compléments/TP3 - Starter.ipynb index 0833b40..eb95e04 100644 --- a/M2/Deep Learning/TP3 - Compléments/TP3 - Starter.ipynb +++ b/M2/Deep Learning/TP3 - Compléments/TP3 - Starter.ipynb @@ -722,7 +722,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.3" + "version": "3.13.9" } }, "nbformat": 4, diff --git a/M2/Deep Learning/TP4 - Récurrents/TP4 - Bonus.ipynb b/M2/Deep Learning/TP4 - Récurrents/TP4 - Bonus.ipynb index 96b0e73..559acf6 100644 --- a/M2/Deep Learning/TP4 - Récurrents/TP4 - Bonus.ipynb +++ b/M2/Deep Learning/TP4 - Récurrents/TP4 - Bonus.ipynb @@ -440,7 +440,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.3" + "version": "3.13.9" } }, "nbformat": 4, diff --git a/M2/Deep Learning/TP4 - Récurrents/TP4 - Starter.ipynb b/M2/Deep Learning/TP4 - Récurrents/TP4 - Starter.ipynb index 8f1d333..d73f589 100644 --- a/M2/Deep Learning/TP4 - Récurrents/TP4 - Starter.ipynb +++ b/M2/Deep Learning/TP4 - Récurrents/TP4 - Starter.ipynb @@ -773,7 +773,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.3" + "version": "3.13.9" } }, "nbformat": 4, diff --git a/M2/Machine Learning/TP_1/2025_TP_1_M2_ISF.ipynb b/M2/Machine Learning/TP_1/2025_TP_1_M2_ISF.ipynb index 62cd9cf..db42065 100644 --- a/M2/Machine Learning/TP_1/2025_TP_1_M2_ISF.ipynb +++ b/M2/Machine Learning/TP_1/2025_TP_1_M2_ISF.ipynb @@ -89088,7 +89088,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.3" + "version": "3.13.9" } }, "nbformat": 4, diff --git a/M2/Machine Learning/TP_2/2025_TP_2_M2_ISF.ipynb b/M2/Machine Learning/TP_2/2025_TP_2_M2_ISF.ipynb index e202adb..0fe3cf4 100644 --- a/M2/Machine Learning/TP_2/2025_TP_2_M2_ISF.ipynb +++ b/M2/Machine Learning/TP_2/2025_TP_2_M2_ISF.ipynb @@ -7016,7 +7016,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.3" + "version": "3.13.9" } }, "nbformat": 4, diff --git a/M2/Machine Learning/TP_3/2025_TP_3_M2_ISF.ipynb b/M2/Machine Learning/TP_3/2025_TP_3_M2_ISF.ipynb index 4908acf..7d19214 100644 --- a/M2/Machine Learning/TP_3/2025_TP_3_M2_ISF.ipynb +++ b/M2/Machine Learning/TP_3/2025_TP_3_M2_ISF.ipynb @@ -4372,7 +4372,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.3" + "version": "3.13.9" } }, "nbformat": 4, diff --git a/M2/Machine Learning/TP_4/2025_M2_ISF_TP_4.ipynb b/M2/Machine Learning/TP_4/2025_M2_ISF_TP_4.ipynb index 3cee985..3a0e4ec 100644 --- a/M2/Machine Learning/TP_4/2025_M2_ISF_TP_4.ipynb +++ b/M2/Machine Learning/TP_4/2025_M2_ISF_TP_4.ipynb @@ -53269,7 +53269,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.3" + "version": "3.13.9" } }, "nbformat": 4, diff --git a/M2/Machine Learning/TP_5/2025_M2_ISF_TP_5.ipynb b/M2/Machine Learning/TP_5/2025_M2_ISF_TP_5.ipynb index 241c0d0..fe6e496 100644 --- a/M2/Machine Learning/TP_5/2025_M2_ISF_TP_5.ipynb +++ b/M2/Machine Learning/TP_5/2025_M2_ISF_TP_5.ipynb @@ -1654,7 +1654,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.3" + "version": "3.13.9" } }, "nbformat": 4, diff --git a/M2/Reinforcement Learning/Lab 1 - Multi‑Armed Bandits with epsilon‑Greedy and Bernoulli Rewards.ipynb b/M2/Reinforcement Learning/Lab 1 - Multi‑Armed Bandits with epsilon‑Greedy and Bernoulli Rewards.ipynb index 9966b7f..65eb276 100644 --- a/M2/Reinforcement Learning/Lab 1 - Multi‑Armed Bandits with epsilon‑Greedy and Bernoulli Rewards.ipynb +++ b/M2/Reinforcement Learning/Lab 1 - Multi‑Armed Bandits with epsilon‑Greedy and Bernoulli Rewards.ipynb @@ -1102,7 +1102,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.3" + "version": "3.13.9" } }, "nbformat": 4,