├── .gitignore └── README.md /.gitignore: -------------------------------------------------------------------------------- 1 | .DS_Store 2 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | ## Cohort 1 Projects 2 | 3 | The project was about exploring the different deeplearning frameworks. We grouped our students into 5 groups, namely TensorFlow, PyTorch, Keras, Neon and Theano. 4 | 5 | 1. Group PyTorch led by George Igwegbe. Other team members include Ezerioha Somtochukwu, Ayodeji Oluwajoba, Chidi, Seun Lawal and Victor O.\ 6 | a. [Article: The Torch Panther](https://medium.com/fbdevclagos/ai6-the-torch-panther-38a778ae8962?) 7 | 8 | 2. Group Tensorflow led by Todun. Other team members includes Ejiro Onose, Tella Babatunde, Ibrahim Gbadegeshin, Juwe C. Raphael and Tunde Osborne \ 9 | a. [Github Link](https://github.com/todun/deep-frameworks-explore/tree/master/tensorflow)\ 10 | b. [Article: May the Tensor Flow with you](https://medium.com/ai-saturdays/aisaturdaylagos-may-the-tensor-flow-with-you-5cdcaad1ddc3) 11 | 12 | 3. Group Theano led by Simon Ubi. Other team members includes Tayo Jabar, Eseme Omole, Lawrence Francis, Kenechi Dukor, Udeme Udofia, Segun Adeleye, Olamiposi Olorunsola, Omoloye Adesina \ 13 | a. [Ancestral Intelligence (AI) with Granny Theano](https://medium.com/ai-saturdays/aisaturdaylagos-ancestral-intelligence-ai-with-granny-theano-fc70ea2e6a7c) 14 | 15 | 4. Group Keras led by Olalekan Olapeju. Other team members include Aderinto Sadiq and Olusegun Komolafe\ 16 | a. [“Karessing” Deep Learning with Keras](https://medium.com/ai-saturdays/aisaturdaylagos-karessing-deep-learning-with-keras-1e9b96d2d013) 17 | 18 | 5. Group Nervana Neon led by Stanley Obumneme Dukor. Other team members include Orevaoghene Ahia, Ejike Richard, Adetola Adetunji, Osho Olumuyiwa, Ahmed Olanrewaju, Moses Ayomide\ 19 | a. [Nervana Neon, the fastest framework alive](https://medium.com/ai-saturdays/aisaturdaylagos-nervana-neon-the-fastest-framework-alive-77e69385ed78) 20 | 21 | 22 | ## Cohort 2 Projects 23 | 24 | ## Cohort 3 Projects 25 | 26 | 1. Machine Learning Track 27 | 28 | 1. Music Popularity Prediction 29 | 2. Using some Economic Factors to predict the Fertility Rate of a Country (United State as a Case Study) 30 | 3. Predicting the market value of premiere league footballers 31 | 4. Car Prize prediction based on age and mileage 32 | 5. Black Friday Price Predictor 33 | 6. Car price predictions using age and mileage 34 | 7. Predicting Outlet Typer Using Big Mart Dataset 35 | 8. Flight Ticket Price Prediction 36 | 9. Regression Model for Fertility Detection Based on Economic Factors 37 | 10. AI16 Salary Predictor Forbes Recruits 38 | 39 | 2. Deep Learning Track 40 | 41 | 1. Image Segmentation 42 | 2. Object Detection 43 | 3. Neural Style Transfer 44 | 4. Face Recognition / Verification 45 | 46 | ## Cohort 4 Projects 47 | 48 | ### 1. Data Science Track 49 | - [Development and Deployement of an Employee Promotion Predictor Model](http://promotion-model.herokuapp.com) by [Taiwo Owoseni](http://twitter.com/thayehas) 50 | - [Assesing issues around poverty in Nigeria](https://github.com/popoolaio/Poverty-in-Nigeria) by Popoola Isiaka Olamilekan, Kosisochukwu Akaeze, Henry Adeyemi, Temitayo Olanrewaju, Oluwaseun Adepegba, Saheed Adetomiwa, Abiodun Quadri and Ehinloju Nike 51 | - [INQUIRY ON THE LIVING STANDARD OF NIGERIANS](https://github.com/sharonibejih/AI-SATURDAY-PROJECT/blob/master/Project%20Analysis.ipynb) by SHARON IBEJIH 52 | - [Solving Poverty through Digital Economy](https://github.com/kayodeakanni/Forthinkn) by Olukayode Akanni 53 | ### 2. Machine Learning Track 54 | - [Exploring MNIST dataset using Tensorflow](https://github.com/Euchigere/Mnist-TensorFlow) by Chigere Emmanuel Ugochukwu 55 | ### 3. Computer Vision Track 56 | - [Sentiment Analysis on Human Faces](http://github.com/Free-tek/Sentiment_Analysis_For_Human_Face) by Adewole Babatunde 57 | 58 | 59 | **Mini-projects** 60 | 1. llcolorizer: a program that uses low-level computer vision techniques to give color to grayscale images 61 | 2. cartoonize: cartoon effect on images 62 | - [llcolorizer and cartoonize](https://github.com/timi-ty/MiniCV) by [timi-ty](https://github.com/timi-ty) 63 | - [cartoonize](https://github.com/aloko001/Cartoonize) by [aloko001](https://github.com/aloko001) 64 | - [llcolorizer](https://github.com/Merkll/llcolorizer) by [Merkll](https://github.com/Merkll) 65 | - [cartoonize](https://github.com/SSInimgba/Computer_Vision/blob/master/Cartoonize_an_Image.ipynb) by [SSInimgba](https://github.com/SSInimgba) 66 | - [cartoonize](https://github.com/Free-tek/Image-Cartoonizer-Computer-Vision/blob/master/Cartoonizer.ipynb) by [Free-tek](https://github.com/Free-tek) 67 | 68 | ### 4. Natural Language Processing Track 69 | - [Text Classification of Clinical notes](http://github.com/itsclint/Dasha) by Mbataku Clinton 70 | - [Anjie - a library for generating corpus in various african languages](http://github.com/Free-tek/Anjie_local_language_corpus_generator) by Adewole Babatunde 71 | 72 | ## Cohort 5 Projects 73 | 74 | ### 1. Data Science and Machine Learning Track 75 | - [Breast Cancer Prediction](https://docs.google.com/presentation/d/1YFAjJcnwV5khvXEQjQ4cmcfPlpI-Rbt4/edit#slide=id.p1) by Blessing Orji, Chidinma Ukaegbu, Damilola Onanuga, Fatimah Salami, Genevieve Nwagwu and Kingsley Makinde 76 | [Video](https://www.youtube.com/watch?v=JkHwrJH_uK4) 77 | - [Red Wine Quality Prediction](https://drive.google.com/file/d/10h-F1FxfEZmZT6kvZc_aNoAvJ7CNf-hD/view) by Olorondu Chizurum, Babatunde koiki, Erinfolami Emmanuel, Sandra Orji, Obiora Maduakor, Sodiq Agunbiade, Modurotolu Olokode, Orutorojo Okiogbero Michael, Shukurat Bello 78 | [Video](https://www.youtube.com/watch?v=DEumopgqjB8) 79 | - [Customer Defection Prediction](https://docs.google.com/presentation/d/178wAFqr_P3OAcbvLBIlN9OU6uejP7HzcGlwdHRj_imE/edit?usp=sharing) by Fortune Adekogbe, Jamiu Alayande, Ademola Atolagbe, Mayowa Oludoyi, Umukulthum Eniafe 80 | [Video](https://www.youtube.com/watch?v=9AZSCKJvbBM) 81 | - [Loan Prediction](https://docs.google.com/presentation/d/1GjwqixzuBEHBH9uAQoEanI_ywheRexZk7yah6A_D_V0/edit#slide=id.gc6f90357f_0_9) by Qodri Hassan, Bosede Ajayi, Raphael Patrick Affiah, Chibueze Joseph 82 | [Video](https://www.youtube.com/watch?v=vwELte5BNjk) 83 | - [Bicycle Sharing](https://docs.google.com/presentation/d/1_L4842lHremgFJWuHBoEOEHphvEGN7BnFS46Wylx3fw/edit?usp=sharing) by Wale Alashe, Faeyi Bilikis Abiola, Idris Lawal, Idris Adeyemi, Victor 84 | [Video](https://www.youtube.com/watch?v=dGkNeN4mzVk) 85 | - [Customer Segmentation](https://docs.google.com/presentation/d/1GjwqixzuBEHBH9uAQoEanI_ywheRexZk7yah6A_D_V0/edit#slide=id.gc6f90357f_0_9) by Olumayowa Omotunde, Olusola Aremu, Simeon Vibbi, Igweonu Chiamaka, Esenwa Chukwudinma, Alo Oluwatobiloba, Misturah Odesanya, Elelu Kehinde , Adekola Kamaldeen 86 | [Video](https://www.youtube.com/watch?v=ZtC1eJRFCd8) 87 | 88 | ### 2. Deep Learning Track 89 | - [Face Emotion Recognition](https://github.com/AI6DLProject/Facial-emotion-classifier/blob/master/Ai6_Facial_Expression_Recognition_Project_Presentation_Slides.pptx) by Ojeifo Oziegbe, Ayodele Adebayo, Kayode Akanni, Praise Taiwo, Sharon Ibejih 90 | [Video](https://www.youtube.com/watch?v=klk2UF_Bd3g) 91 | - [An English Chatbot](https://github.com/kosi-so/Simple-Chatbot-with-Pytorch) by Akaeze Kosisochukwu 92 | [Video](https://www.youtube.com/watch?v=klk2UF_Bd3g) 93 | 94 | 95 | ## Community Inspired Projects 96 | 1. [Easy Neural Style Transfer With Google Colab](https://medium.com/@lawrencedikeu/easy-neural-style-transfer-with-google-colab-a3264789d6ed) by Lawrence Francis 97 | 98 | 2. [Image Classification with Fast AI](https://medium.com/@kennydukor/image-classification-with-fast-ai-at-last-something-that-works-with-little-effort-56d3abe7c542) by Kenechi Franklin Dukor 99 | 100 | 3. [QR-based Attendance Tracka](http://#) by Tejumade Afonja and Kenechi Franklin Dukor _(soon open-sourced)_ 101 | 102 | ## Kaggle Hackathons 103 | 1. [Lagos AI Hack: Chow Land](https://www.kaggle.com/c/lagos-ai-hackathon) organized in partnership with Lagos Women in Machine Learning and Data Science 104 | 105 | 2. [Lagos AI Hack2: Predict Hourly Taxi Ride](https://www.kaggle.com/c/lagosaihackathon) organized in partnership with InstaDeep and Lagos Women in Machine Learning and Data Science. 106 | 107 | 3. [HackExpo - Road Traffic Congestion](https://www.kaggle.com/c/hackexpo2018) organized in partnership with DeepQuest AI. 108 | 109 | 110 | ## CohereAIHack Hackathon Projects 111 | 1. [Multilingual Semantic Search for Video](https://github.com/lawalbolaji/Multilingual-Semantic-Search-for-Video/tree/main) 112 | 2. [Content Moderation Cohere AI App](https://github.com/fMurugi/content-moderation-cohere-ai-app/tree/master) 113 | 3. [Dobby](https://github.com/beesaferoot/dobby) 114 | 4. [Cohere Text Classifier for Customer Service Ticket Classification](https://github.com/faisalm93/requestclassifier) 115 | 5. [Multilingual Content Generator](https://github.com/alaminmagaga/contentgenerator) 116 | 6. [Cohere Parallel Language Sentence Alignment](https://github.com/lukmanaj/Cohere-Parallel-Language-Sentence-Alignment/tree/main) 117 | 7. [Document CoFinder](https://github.com/KayO-GH/Document-Semantic-Search) 118 | 8. [Bible App](https://github.com/Ramond-king05/Data-Geeks) 119 | 9. [Content Generator and Summarizer](https://github.com/abiola9525/Cohere_AI-AI-Saturday-Hackathon) 120 | 10. [Cross-Lingual Similarity and Semantic Search with Cohere Multilingual API](https://github.com/Muhammad0isah/SemanticSearch) 121 | 11. [Internal Health](https://github.com/Tosin5S/team-coherent) 122 | 12. [Teaching and Learning made easy with cohere ai](https://github.com/gabrielzencha/cohere_hackathon) 123 | 13. [Multilingual African News Clustering and Semantic System](https://github.com/teejay13/AfriNews_Cluster) 124 | 14. [Nexus News](https://github.com/bideeen/NewsNexus/tree/main) 125 | 15. [MultiLingo Multilanguage Text Summarization for Everyone](https://github.com/Aybee5/MultiLingo) 126 | 16. [Òmòwé.ai](https://github.com/Paulooh007/omowe.ai) 127 | 128 | ### Articles Inspired by the Community 129 | 1. [Ripples of the Wave of Change](https://medium.com/ai-saturdays/ripples-of-the-wave-of-change-95178e728d0b) by Olalekan Olapeju 130 | 131 | 2. [Leveraging on Google Colab](https://medium.com/ai-saturdays/aisaturdaylagos-leveraging-on-google-colab-313bab053603) by Owoeye Gabriel 132 | 133 | 3. [Classification of Nigeria Currency Notes Using Fastai Framework](https://medium.com/ai-saturdays/aisaturdaylagos-classification-of-nigeria-currency-notes-using-fastai-framework-2fdcedc174e0) by Kenechi Franklin Dukor 134 | 135 | 4. [Basic Overview of Convolutional Neural Networks](https://medium.com/dataseries/basic-overview-of-convolutional-neural-network-cnn-4fcc7dbb4f17?) by Udeme Udofia 136 | 137 | 5. [The Brain and the Model](https://medium.com/@kennydukor/the-brain-and-the-model-c82ff48f9867) by Kenechi Franklin Dukor 138 | 139 | 6. [Lagos AI Hackathon 1](https://medium.com/ai-saturdays/aisaturdaylagos-lagosaihack-8479b3f53169) by Tejumade Afonja 140 | 141 | 7. [Lagos AI Hackathon 2](https://medium.com/ai-saturdays-lagos-articles/lagos-ai-hackathon-lagosaihack-2nd-edition-d4258c662d51) by Tejumade Afonja 142 | 143 | 8. [HackExpo — Into the future](https://deepquestai.com/HackExpo/) by DeepQuest AI 144 | 145 | 9. [Bridging the Artificial Intelligence (AI) Gap with AISaturdays](https://medium.com/ai-saturdays/bridging-the-artificial-intelligence-ai-gaps-with-ai6-9a5cf0b910f8) by Tejumade Afonja 146 | 147 | 148 | ## Recaps on Classes 149 | 1. [Cohort 1, Week 2 Recap](https://medium.com/ai-saturdays/aisaturdaylagos-recap-on-week-2-8bf253802796) written by Tejumade Afonja and Femi Azeez 150 | 2. [Cohort 1, Week 3 Recap](https://medium.com/ai-saturdays/aisaturdaylagos-recap-on-week-3-b463396f2140) written by Tejumade Afonja and Femi Azeez 151 | --------------------------------------------------------------------------------