Intro to Deep Learning with PyTorch By Facebook AI

✅ Free Course

#Deep_Learning #DL #PyTorch

🌎 Link Review

🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN
❇️ @AI_Python

Model evaluation, model selection, and algorithm selection in machine learning

#ML #AI #BigData #DL ##neuralnetworks

🌎 Link Review

🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN
❇️ @AI_Python

New NLP News:

ML on code, Understanding RNNs, Deep Latent Variable Models, Writing Code for NLP Research, Quo vadis, NLP?, Democratizing AI, ML Cheatsheets, Spinning Up in Deep RL, Papers with Code, Unsupervised MT, Multilingual BERT

#NLP #ML #DL #Training #RNN #RL

🌎 Link Review


🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN
❇️ @AI_Python

Guide to learn DataScience and MachineLearning with Python:
#ML #DL
#منابع #علم_داده
---START---

✅ Step 1

🔸 Download and Install Anaconda

✅ Step 2
a. Learn the basics of Python (Lists, Tuples, Dictionaries, etc)
b. Understand the basics of data structures and algorithms :

🌎 Link Review
---Beginner Level Completed---

✅ Step 3
a. Understand the use of regular expressions
🔸 Do more practice problems in PythonHacker Rank
🔸 Codeacademy

✅ Step 4
Learn the scientific libraries (NumPy, SciPy, Pandas)
🔸 Pandas

✅ Step 5
Data Visualization (Matplotlib, plotly, seaborne, etc…)
🔸 Matplotlib
🔸 Python Gallery
---Intermediate Level Done---

✅ Step 6
🔸Machine Learning with Scikit-LearnMachine Learning in 20min
🔸 Skcikit-Learn Tutorial

✅ Step 7:
Practice your machine learning skillsKaggle Machine Learning Tutorial
---Advanced Level Completed--

✅ Step 8:
Deep Learning
Deeplearning.ai (Andrew Ng)

🔸 Kaggle Deep Learning Tutorial

❇️ @AI_Python
✴️ @AI_Python_EN

A Concise Handbook of TensorFlow (https://tf.wiki ) Online book for those who already knows #ML / #DL theories and want to focus on learning #TensorFlow itself

https://tf.wiki/en/preface.html

❇️ @AI_Python_EN
🗣 @AI_Python_arXiv
✴️ @AI_Python

A Brief History of #Artificialintelligence by
🔗http://bit.ly/2oNyCGm #MachineLearning #ML #Robotics #Algorithms #Analytics #NeuralNetworks #NLP #BigData #DataScience #DeepLearning #DL #RT

🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN

What are the best resources to learn major libraries for #DataScience in #Python. Here is my updated full list.
Will recommend to use Jupyter-Spyder environment to practice all these.

#DataLoading and #DataManipulation

✔️Numpy - https://bit.ly/1OLtuIF
✔️Scipy - https://bit.ly/2f3pitB
✔️Pandas - https://bit.ly/2qs1lAJ

#DataVisualization
✔️Matplotlib https://bit.ly/2gxxViI
✔️Seaborn https://bit.ly/2ABypQC
✔️Plotly https://bit.ly/2uJwULB
✔️Bokeh https://bit.ly/2uOFbxQ

#ML #DL #ModelEvaluation
✔️Scikit-Learn - https://bit.ly/2uYFNkw
✔️H20 - https://bit.ly/2M0hJnG
✔️Xgboost - https://bit.ly/2M3Vdut
✔️Tensorflow - https://bit.ly/2vfI5es
✔️Caffe- https://bit.ly/2a05bgt
✔️Keras - https://bit.ly/2vfDyZj
✔️Pytorch - https://bit.ly/2uXWY5U
✔️Theano - https://bit.ly/2v3N805


#analytics #artificialintelligence #machinelearning
#recommend

✴️ @AI_Python_EN