SoftEng's Posts
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Hello everyone, I just stumbled upon Data Science Nigeria 2018 plans. It's really packed with loads to data science goodies and I advise you try participating in one or more events. I really like this initiative, well done to the Data Science Nigeria team. Below is the link http://www.datasciencenigeria.org/2018plan/ Extra Note For those who don't know about Data Science Nigeria prior to this post, I apologise. I remember mentioning about the intiative on another AI/ML related thread, but not on this thread prio to this comment. Later in the day, I will curate a list of other Nigerian/African related AI/ML/Data-Science communities or initiatives for you all to check out. Thanks. |
Happy New Year to everyone in this group. Stay blessed. ![]() |
4kings:Even though my recent project have been computer vision based (computer vision for video related tasks), I haven't seriously looked into Object Detection Tasks and I haven't read the YOLO paper. Previously, I heard about R-CNN and its variant, but I've been recently reading comments about YOLO recently (I didn't even know it plays in thesame space with R-CNN until your question). I have been hearing about YOLO in relation to the [url]deeplearning.ai[/url] coursera courses, and I suppose the explanation in this 7mins video should do justice explaining YOLO. |
ruffhandu:I haven't used Watson API and I can only contribute very little. Please for those who have used (or played) with Watson, comment on this. Even if you haven't used Watson, but have worked on conversational bots where you have "Entity" and "Intent" components, please comment. The Watson API follow similar parttern. @ruffhandu A link to wherever we can test what you are working on may be helpful in advising you appropriately. My contribution I am not sure how much work or material you have covered before your question, but here's a link to a getting started guide for Watson Conversational (system). If you have already gone through this material before now, then I apologise. If not, I recommend you check it out. https://console.bluemix.net/docs/services/conversation/getting-started.html#gettingstarted Additionally, you can also look through the codes of some examples in the link below. It may give you some ideas on how to fix issue(s) in the bot that you are building. https://console.bluemix.net/docs/services/conversation/sample-applications.html#sample-apps Thanks. |
raymod170:OK. That's good. Well done. I remembered you mentioned you are a .NET developer from an earlier comment. I did a quick search for a pandas library equivalent in .NET and the library below was one of the results. Therefore, just in case you want to further pursue using a pandas-like library in .NET, then it may be worth exploring as well. http://bluemountaincapital.github.io/Deedle/ |
kanirip:Sure thing. Thanks for your interest. We discuss here on Nairaland. The (simple) requirements of the group are on the first page of this post (i.e.first comment on page 0) Feel free to make contributions by raising discussions about AI related ideas/projects/research or ask questions or answer questions of others. Thank you. |
J0nyb0y:j0nyb0y, Below are some links I found. Most of the materials are old. I was not too sure how to get recent information relevant to your context (I was seeing stuffs related to fuzzy-logic/rules). I believe it's just lack of proper vocabulary or the right keyword to check for. Looking through list of references in paper may be a way to get other relevant materials 1. Knowledge Management: Practices and Challenges http://libres.uncg.edu/ir/uncg/f/L_Iyer_Knowledge_2000.pdf 2. Security Considerations for Knowledge-Based Systems - 1987 https://www.researchgate.net/publication/275522171_Security_Considerations_for_Knowledge-Based_Systems Note: You may need to login/create-an-account with research gate to download. 3. Multilevel security for knowledge based systems http://www.dtic.mil/get-tr-doc/pdf?AD=ADA234974 Other links not related to security challenges in Knowledge Based System, but contains discussions about techniques used in KBS are listed below. Even though they are not related to security challenges, you can still extract some useful information that may inform you about security challenges in KBS, or lead you to other materials that can provide such (this is more of researching activity). 1. This document is quite recent (2013), and it talks about apply ant colony optimization knowledge based expert system http://www.sciencedirect.com/science/article/pii/S0950705112002985 free link to pdf https://pdfs.semanticscholar.org/0028/8ba713416d6a4f9d402bd1ce76c2d6108b28.pdf 2. The link below contains document describing KBS in general, but it's very old (and I think it might really oversell the points raised) https://www.researchgate.net/profile/B_Chandrasekaran/publication/3282122_Generic_Tasks_in_Knowledge-Based_Reasoning_High-Level_Building_Blocks_for_Expert_System_Design/links/54fd651c0cf2c3f52424a31b.pdf |
raymod170:You can try one of the following: 1. if you can use python, then I'll suggest you checkout pandas library. I believe it meets the requirements of what you are trying to achieve. Even though I haven't used extensively, I believe it's a mature and easy to use library. 2. check for online converter "csv to sql". (I don't know if such converter exist, but it's worth the try) 3. opening the csv file in excel, save to microsoft access format, and then check if you can convert the data to sql from microsoft access. |
4kings, j0nyb0y Thanks. Additionally, thanks 4kings as you have contributed a lot in the group already. Thanks to raymod170 and Samcent as well. I'm hoping that others in the group will become more active (maybe after Christmas and New Year celebration). Please, we need more people to participate. It does not have to be questions and answers alone. If you have some interesting project/research, please feel free to share. Thanks all. Dmayor7, osarenomaspecial, unphilaz, shams040, lum1, kelvine95, rayval, Ibroh24, BunchObute, NaHiim, EbonyMira, themonk7, Unmarshalled, Omoadeola, lydia4211 and others Hope you are all fine? |
I hope the above description clears the air with respect to knowledge engineering definition. If that's the case, then let's move on to the question by j0nyb0y. The question is about Classical AI systems, which was specified as out of context of this thread based on the requirements defined at the beginning this thread. I have the impression that you did not know that discussions about knowledge engineering as a part of classical AI, therefore I'll let this one slide. We will continue the discussion to help you with your project. One of the few examples of expert system we were taught in school is called MYCIN (for healthcare) you can look into security challenges in that area. I'll try to do some online search about Security Knowledge Based systems later in the day (or tomorrow) and report back here. Here's a interesting idea that comes to mind. If you finally identify a security challenge, you can design another knowledge based system or machine learning system that combats the challenges. I don't know how it's going to work, but it may be interesting. Thank you all. |
Longer Version The most common type of knowledge based system is an expert. Most times, this knowledge they talk about are encoded as rules (if... then... else... statements). Note: This rule-based structure of representing knowledge are similar to decision tree technique in Machine Learning. However, the main difference is that the rules in a decision tree (i.e. branches) are learned from your dataset, while the rules in the knowledge base of an expert system are explicitly design/encoded/programmed/specified by the programmer/knowledge-engineer. The idea of knowledge engineering is part of Classical AI systems where Expert Systems (mostly rule based) was the most popular. Knowledge Engineering Vs Data Engineering Knowledge engineering is a sub part of Knowledge Based System just as Data Engineering is a part of Data Science. The both have some similarities and differences. Similarities 1. They are both involved in data acquisition in the specific domain (e.g. health care, weather forecast, business etc) in their respective field. Knowledge engineer acquires data by: interviewing human expert with domain knowledge, (electronic) records and so on. Since the role of a data engineer (mostly data scientist as well) in exists more recently, they acquire data mostly from electronic records (especially from database and large data storage software tools like hardoop and spark) by data pipeline software built by themselves. Differences Once the data is acquired, their roles start differing. 1. Knowledge engineer starts analyzing the data, preprocesses it and then manually design the rules which will be programmed into the knowledge base. The knowledge engineer also has to think about how the knowledge is stored and represented in the knowledge base. On the other hand, the data engineer (data scientist) "cleans" the data, analyze and visualise the data, removes unwanted features and then employs a machine learning algorithm that automatically produces a model (which can be viewed as implicitly defined rules) by learning from the data. I agree that some of the analysis process for data engineering is similar to knowledge engineering as well. However, I guess what differentiates them is the technologies/tools employed in the process. Software tools used at the time knowledge engineering was popular may not be same with what's currently being used in data engineering. 2. In recent times, there has been ongoing discussion about bias (e.g. race, ethnicity, gender, financial status etc) in AI algorithm. Therefore, in terms of biasness, here's what I can deduce (my personal opinion) : Data Engineering mostly encodes bias from data (the dataset being learned from), however Knowledge Engineering encodes the bias of the data and that of the knowledge engineer. Conclusion To some extent, Knowledge Engineering is to Knowledge Base (and Expert Systems) as Data Engineering is to Models learned from data (Data Science / Machine Learning). Additionally, Knowledge Engineering is to Classic AI as Data Engineering is to Modern AI. |
4kings, raymod170, j0nyb0y well done on the discussions. I agree with some points raised by raymod170, however I'm not sure knowledge engineering can be viewed as a parallel of NLP (I may be wrong on this). Also, I understand 4kings perspective as well as the perspective of raymod170. I'll try to bridge both by comparing / contrasting both. Please bear with me, may be lengthy. TL; DR Data Engineering is sub part of data Science with focus on acquiring data, as well as cleaning and analyzing data. The output of data engineering process is fed into a machine learning algorithm to produce a model (that contains implicit rules not directly programmed by humans) . It is part of modern AI toolset. Knowledge Engineering is a sub part of Knowledge Based System (a type of Classical AI) that focus on acquiring (and analyzing) and also manually encoding/programming knowledge from the data as rules (if statements). The rules are programmed directly by humans. |
4kings and Samcent both of you have been excellent providing help to odizeey. well done. Samcent, I'm not sure why you posted your last comment. So far, the discussions between 4kings and yourself have been good and constructive. No cause to upset anyone. Please keep the discussions rolling. Thank you all. |
odizeey:I've looked through kaggle to get a feel of the Complete Player dataset. I'm guessing you're referring to one of the links down below (I'm not sure the exact one). If the above is correct, then there is no clear cut pre-defined task for the dataset (i.e. no clearly a classification or a regression problem). Based on Exploring Data section in authors description, it may seem that they provided the dataset for mainly analysis/visualisation of the dataset. However, people can work on many different types of tasks as evident in Kernels section of each dataset link. For example, predicting player position, which is a classification task. In case you are not sure where to start, checkout the Kernels section of each dataset. The kernel section contains codes of tasks people worked on. You can read through their code/tutorial and run the code as well. This should help you improve your skills. You can also check out the "Discussion" section of the dataset link, which should give you a some additional ideas of what people are working on, questions raised etc. Short Note On Data Analysis/Visualisation Data analysis/visualisation is a key preliminary step in any datascience project. It enables you (the data scientist) to get a good feel (and other useful information such as mean and variance of the dataset distribution). Additionally, through data analysis/visualisation you may be able to find out duplicate features in samples of your dataset as well as eliminate or reduce the number of features in samples of your dataset. Usually, after data analysis/visualisation stage, the data scientist is better equipped to select the right kind of machine learning model (e.g. random forest, gradient boosting, neural network and so on) that may work best for the dataset. Links 1. https://www.kaggle.com/thec03u5/fifa-18-demo-player-dataset 2. https://www.kaggle.com/artimous/complete-fifa-2017-player-dataset-global 3. https://www.kaggle.com/kevinmh/fifa-18-more-complete-player-dataset |
Hi all, Thanks to everyone who gave their opinion with regards to which platform (e.g. Nairaland, Telegram, Whatsapp, Slack etc) the group should use. I conclude that we should keep discussion here on Nairaland. No need to migrate elsewhere. The main benefit I envisage in staying on Nairaland is openness. Openness, meaning that our discussions can be viewed by the public (both to interested and non-interested persons) and the possiblity of this thread popping up on search engine results for anyone who search for Artificial Intelligence (AI) and Machine Learning (ML) community or group in Nigeria. Thanks all. Looking forward to all the ideas/research/projects/discussions that will unfold over time. |
4kings:Alright. Good luck. You should also checkout http://www.maluuba.com/research/ as suggested by osarenomaspecial |
@Dell031 I earlier shared the below post. It should give help you extract some points (like a "soft table of content" about topics you need to go through.Thanks. SoftEng: |
omokoladejames:I agree with you that we have conclude on matters related to platform. Thtat's why I have been asking for suggestions from everyone who showed interest in this group. Eveeryone's suggestion becomes some sort of poll or vote and the platform that has the highest number of suggestion should be used. However, not many persons have suggested or contributed any comment to discussion centering around platforms. Please everyone should comment. I don't want us to take a decision based on 1 or 2 suggestions only. Thank you. cc: Dmayor7 osarenomaspecial unphilaz shams040 Samcent islamics lum1 kelvine95 4kings rayval Ibroh24 BunchObute NaHiim EbonyMira themonk7 Unmarshalled Omoadeola lydia4211 |
islamics:OK. All the best with your Android study. |
Chukwudaalu:Do you have any platform suggestion in mind? BTW, we can also share articles, videos etc via links on Nairaland as well. |
Unmarshalled:OK. You are welcomed to continue to be part of the group. |
sirdouglas:I guess the issue is as a result of a line in your code that has been hard coded with an absolute file path that is specific to your local development machine. Possible Solution Try to locate the line in your code (I advice you start from your index.php) where you have the absolute file path "C:\wamp\www\numac2/templates/shaper_awetive/less/master.less" and then replace it with relative file path (which should work on both your local development machine, and on any computer the code is hosted) "./templates/shaper_awetive/less/master.less" Good luck |
Unmarshalled:I won't advice you drop js. You can use any language to start learning Machine Learning (ML). There's even a deep learning (a subset of machine learning) library for js called https://deeplearnjs.org/. However, it is easier to use the language used by the resource (video lectures or blogposts) from which you are learning. Lastly, you mentioned in your last post that you were learning js to enable you create PWAs. I assume you mean Progressive Web Applications and if that's the case, then I'll advice you stick to one thing (PWAs or Machine Learning) for now and learn it to level where you can at least work on a simple project and then you can afterwards move on to the next thing. Don't try to learn both PWAs and ML at the same time. It's just my opinion, nothing more. You can still choose to do both (PWAs and ML). Thanks. |
4kings:I didn't want to comment on this because of my limited knowledge in NLP. The only area(task) that I have dabbled into in the past is Language Modeling. However, from what I remember Question Answering Systems (QAS) are still very much limited as researchers have not been able to get it to practically work well on open ended domain. This does not mean that it doesn't work, but it just very hard right now. It's does not work practically well compared to Language Translation task which works well. Here's something that maybe useful to you. Amazon hosts an Alexa Prize competition (https://developer.amazon.com/alexaprize) for universities around the world to build a conversational agent (which is atleast similar to QAS, if not thesame). You can check out the 2017 prize winner and read through their paper or blog post (if available) to see the techniques used. Who knows, if they decide to open it to candidates outside universities, you can form a group here that can participate as well. Below are 2 additional links (not related to the competition) that you might find useful https://aws.amazon.com/blogs/ai/creating-a-question-and-answer-bot-with-amazon-lex-and-amazon-alexa/ https://aws.amazon.com/blogs/aws/announcing-the-aws-chatbot-challenge-create-conversational-intelligent-chatbots-using-amazon-lex-and-aws-lambda/ [url]Question[/url] Do you have any dataset in mind that you want to use to train your QAS? Final Note I once watched a video where a top NLP scientist mentioned that QAS are like crown jewel of NLP because a fully functional QAS should be able to perform other NLP tasks (e.g. you can ask a QAS to translate a text from one language to another, or you can ask a QAS to summarize text) |
omokoladejames:Yeah, we all need to discuss about the platform issue. We need to decide whether we continue here on Nairaland or else where. Thank you for your suggestion. Still waiting for other suggestions. |
Unmarshalled:4kings thanks for your input. Suggestions from others are also welcomed. My Suggestion In addition to 4kings suggestion, the links below are short blog posts that gives some perspective. 1. https://www.digitalocean.com/community/tutorials/an-introduction-to-machine-learning (gives a very high level introduction to Machine Learning) 2. https://www.toptal.com/machine-learning/machine-learning-theory-an-introductory-primer (similar to the first link, but goes a little bit deeper, with very little amount of math to describe the algorithm that powers some methods) Lastly, if you more interested in getting a well rounded knowledge (not just high level overview), then any 1. If you are interested in first getting a rounded knowledge about Machine Learning, then link below is a good introduction https://www.coursera.org/learn/machine-learning. The course is video based, so you will need a fair amount of internet data. 2. If you can't do video (because of data), the website below is also nice, but you will need to browse through it (especially the blog section) to mine useful information from it. 3. The link below (machine learning cheat sheet with much emphasis on neural networks) may also be nice. https://ml-cheatsheet.readthedocs.io/en/latest/index.html |
The new thread for the group has now been created. Visit here https://www.nairaland.com/4237475/artificial-intelligence-machine-learning-group. This survey thread is now closed. Thank you. |
TL;DR A group with persons interested in Artificial Intelligence and Machine Learning. New members (beginners and experts) are welcome to join. See requirements below. Thank you. Hi, As a follow up to the survey on this thread https://www.nairaland.com/4209747/survey-people-interested-artificial-intelligence, this thread has been created since we had more than 10 persons interested in this group. One point raised in the survey thread was about the potential of using whatsapp as the group's platform. We can discuss about this here (there are several platforms to consider; nairaland, whatsapp, google group, slack etc). Lastly, this post on this thread kick starts the group, therefore, anyone with any discussions/questions/projects can jump right in. Thank you all. QUICK REMINDER Requirements To ensure you know what you are getting into, below is a list of requirements for interested persons a. Interested in discussions/developments/research about modern AI systems only (see note below for description about what counts as mordern AI). b. Serious minded c. That's all about requirement. :-) Important Points to Note a. I'm not here to teach you about AI/ML. No, it's not a one sided thing. We all contribute and learn from each other about the current AI/ML projects/research that you're are working on. The aim is to foster a community of AI developers/researchers in Nigeria. b. Modern AI (as opposed to classical AI which includes subjects like travelling salesman problem, breadth first search, simple puzzle solver etc.) focus on Machine/Deep Learning techniques (e.g. neural networks) being applied to areas such as computer vision tasks (e.g. image classification/localization), natural language processing tasks (e.g. language translation), speech recognition tasks (e.g. speech-to-text), control/planning tasks etc. c. I know there exist AI/ML related forums online that bring together people from different countries (such as this reddit group [3]). However, I feel we need to do something more local to foster an AI community here in Nigeria. d. I'll try to keep this thread in the front page of the programming section daily by so as to get enough viewers as possible. cc: Dmayor7 osarenomaspecial unphilaz shams040 Samcent islamics lum1 kelvine95 4kings rayval omokoladejames Ibroh24 Chukwudaalu BunchObute NaHiim EbonyMira themonk7 Unmarshalled Omoadeola lydia4211 |
@4kings, @Unmarshalled and @everyone. I apologise for the delays. Since we have more than 10 persons interested in the group, I'll go ahead an create a thread now on Nairaland as earlier stated. @4kings thanks for your inputs so far. |
The survey is now closed. We have a total of 17 persons (18 if I include myself) that indicated their interest in the formation of the AI/ML group. Thanks for everyone who showed interest. If anyone else is interested in the group, please feel free to jump right into the new thread and introduce yourself. I'll put a link to the new thread here when it's created. I'll create a thread here on nairaland for the group and will cc (mention) interested person on that thread. We can then discuss on that thread how to proceed and what platform (e.g. nairaland, whatsapp, google group, slack etc) will be preferable. Recall some important points as stated earlier: Important Points to Note a. I'm not here to teach you about AI/ML. No, it's not a one sided thing. We all contribute and learn from each other about the current AI/ML projects/research that you're are working on. The aim is to foster a community of AI developers/researchers in Nigeria. b. We will focus on Modern AI and its application rather than classical AI systems. Thank you all. |
4kings: ![]() |
themonk:Sure thing. we can do that when the thread for the group is created. With regards to platform, I believe it should be the decision of the group when created. Thanks. |


about topics you need to go through.