ajtheb

ajtheb's Stars

• freeCodeCamp/freeCodeCamp

  freeCodeCamp.org's open-source codebase and curriculum. Learn to code for free.

  Language:TypeScript401k8.6k18.2k37.1k

• TheAlgorithms/Python

  All Algorithms implemented in Python

  Language:Python184k5.9k1.5k44.3k

• jakevdp/PythonDataScienceHandbook

  Python Data Science Handbook: full text in Jupyter Notebooks

  Language:Jupyter Notebook42.8k1.8k19217.8k

• TencentARC/GFPGAN

  GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.

  Language:Python35.5k5034715.9k

• TheAlgorithms/C-Plus-Plus

  Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.

  Language:C++30.1k5092897.1k

• ChristosChristofidis/awesome-deep-learning

  A curated list of awesome Deep Learning tutorials, projects and communities.

  23.6k1.2k216k

• youssefHosni/Data-Science-Interview-Questions-Answers

  Curated list of data science interview questions and answers

  3.2k563731

• asappresearch/sru

  Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755)

  Language:Python2.1k64133308

• nivu/ai_all_resources

  A curated list of Best Artificial Intelligence Resources

  Language:Jupyter Notebook937301226

• tdpetrou/Machine-Learning-Books-With-Python

  Chapter by Chapter notes, exercises and code for a variety of machine learning books using Python

  Language:Jupyter Notebook931550586

• Shark-NLP/DiffuSeq

  [ICLR'23] DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models

  Language:Python711267987

• aasu14/Data-Science-Hackathon-And-Competition

  Grandmaster in MachineHack (3rd Rank Best) | Top 70 in AnalyticsVidya & Zindi | Expert at Kaggle | Hack AI

  Language:Jupyter Notebook209100116

• aehuynh/hidden-markov-model

  First order HMM with Viterbi, Forward-Backward and Baum-Welch implementations

  Language:Python483049

• nishantkr18/Dynamic-Gesture-recognition-system

  Hand gesture extraction using background elimination followed by recognition through convolutional neural networks.

  Language:Python21335

• daijiang/Linear_Algebra_notes

  Notes from [lectures](https://www.youtube.com/playlist?list=PLE7DDD91010BC51F8) taught by Prof. Gilbert Strang

  11404

• yashshah14093/REAL-TIME-FORECAST

  Implemented an LSTM based deep learning model using Keras API for Predicting Hourly Electricity Consumption of a region. Analyzed the variation in electricity consumption with time and climatic conditions using Seaborn. Trained the model on the data of the past three years of electricity consumption and climate conditions. Achieved a test-set Root Mean Square Error(RMSE) of 2.33.

  Language:Jupyter Notebook40

• yashshah14093/Data-Structures-and-Algorithms

  Language:Java2100

• yashshah14093/Image-Compression

  Language:Jupyter Notebook2102