Cython - Revision history

BPeat at 03:57, 2 March 2024

2024-03-02T03:57:56Z

BPeat at 20:30, 3 July 2023

2023-07-03T20:30:08Z

BPeat: Text replacement - "http:" to "https:"

2023-03-28T12:35:10Z

Text replacement - "http:" to "https:"

BPeat: /* Fast natural language processing (NLP) with spaCy */

2019-04-14T19:45:46Z

‎Fast natural language processing (NLP) with spaCy

BPeat at 02:06, 3 February 2019

2019-02-03T02:06:36Z

BPeat at 11:59, 5 January 2019

2019-01-05T11:59:00Z

BPeat: /* Fast natural language processing (NLP) with spaCy */

2018-08-31T19:35:03Z

‎Fast natural language processing (NLP) with spaCy

BPeat at 19:33, 31 August 2018

2018-08-31T19:33:47Z

BPeat at 19:27, 31 August 2018

2018-08-31T19:27:21Z

BPeat at 19:25, 31 August 2018

2018-08-31T19:25:02Z

@@ Line 27: / Line 27: @@
 === Fast natural language processing (NLP) with spaCy ===
-C Programming for Machine Learning - The ability to write implementations of machine learning algorithms in pure C allows developers to very efficiently manage memory allocation, concurrency, and control flow. That means fast implementations that can outperform preexisting models in other languages, including even (gasp) Python. It’s a useful skill to know and in this live stream I’ll use C and C-based Python tools like Cython + spaCy to develop some really fast natural language processing algorithms for text data. We’ll be able to tokenize, tag, normalize, vectorize, and dependency parse articles of text to derive valuable insights. No installation necessary, we'll do this together using Google Colab in the browser.
+C Programming for Machine Learning - The ability to write implementations of machine learning algorithms in pure C allows developers to very efficiently manage [[memory]] allocation, concurrency, and control flow. That means fast implementations that can outperform preexisting models in other languages, including even (gasp) Python. It’s a useful skill to know and in this live stream I’ll use C and C-based Python tools like Cython + spaCy to develop some really fast natural language processing algorithms for text data. We’ll be able to tokenize, tag, normalize, vectorize, and dependency parse articles of text to derive valuable insights. No installation necessary, we'll do this together using Google Colab in the browser.
 * [[spaCy]]

@@ Line 2: / Line 2: @@
 |title=PRIMO.ai
 |titlemode=append
-|keywords=artificial, intelligence, machine, learning, models, algorithms, data, singularity, moonshot, Tensorflow, Google, Nvidia, Microsoft, Azure, Amazon, AWS
+|keywords=ChatGPT, artificial, intelligence, machine, learning, GPT-4, GPT-5, NLP, NLG, NLC, NLU, models, data, singularity, moonshot, Sentience, AGI, Emergence, Moonshot, Explainable, TensorFlow, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Hugging Face, OpenAI, Tensorflow, OpenAI, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Meta, LLM, metaverse, assistants, agents, digital twin, IoT, Transhumanism, Immersive Reality, Generative AI, Conversational AI, Perplexity, Bing, You, Bard, Ernie, prompt Engineering LangChain, Video/Image, Vision, End-to-End Speech, Synthesize Speech, Speech Recognition, Stanford, MIT |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
 |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
 }}
 [https://www.youtube.com/results?search_query=Cython Youtube search...]
@@ Line 9: / Line 18: @@
 * [[Python]]
 Cython: Blend the Best of Python and C++  ...superset of Python in C Programming.

@@ Line 5: / Line 5: @@
 |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
 }}
-[http://www.youtube.com/results?search_query=Cython Youtube search...]
+[https://www.youtube.com/results?search_query=Cython Youtube search...]
-[http://www.google.com/search?q=Cython+machine+learning+ML+artificial+intelligence ...Google search]
+[https://www.google.com/search?q=Cython+machine+learning+ML+artificial+intelligence ...Google search]
 * [[Python]]

@@ Line 21: / Line 21: @@
 * [[spaCy]]
 * [[Natural Language Processing (NLP)]]
-* Google [[Colaboratory]]
+* Google [[Colaboratory]] (Colab)
 <youtube>giF8XoPTMFg</youtube>

← Older revision		Revision as of 02:06, 3 February 2019
Line 1:		Line 1:
		+	{{#seo:
		+	\|title=PRIMO.ai
		+	\|titlemode=append
		+	\|keywords=artificial, intelligence, machine, learning, models, algorithms, data, singularity, moonshot, Tensorflow, Google, Nvidia, Microsoft, Azure, Amazon, AWS
		+	\|description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
		+	}}
	[http://www.youtube.com/results?search_query=Cython Youtube search...]		[http://www.youtube.com/results?search_query=Cython Youtube search...]
		+	[http://www.google.com/search?q=Cython+machine+learning+ML+artificial+intelligence ...Google search]

	* [[Python]]		* [[Python]]

← Older revision		Revision as of 19:33, 31 August 2018
Line 13:		Line 13:

	* [[spaCy]]		* [[spaCy]]
		+	* [[Natural Language Processing (NLP), Natural Language Inference (NLI) and Recognizing Textual Entailment (RTE)]]
		+	* [[Colaboratory]]

	<youtube>giF8XoPTMFg</youtube>		<youtube>giF8XoPTMFg</youtube>
−
−	~~spaCy:~~
−	~~<youtube>gJJQs47aUQ0</youtube>~~
−	~~<youtube>sqDHBH9IjRU</youtube>~~
−	~~<youtube>Y90BJzUcqlI</youtube>~~
−	~~<youtube>jB1-NukGZm0</youtube>~~

← Older revision		Revision as of 19:27, 31 August 2018
Line 11:		Line 11:

	C Programming for Machine Learning - The ability to write implementations of machine learning algorithms in pure C allows developers to very efficiently manage memory allocation, concurrency, and control flow. That means fast implementations that can outperform preexisting models in other languages, including even (gasp) Python. It’s a useful skill to know and in this live stream I’ll use C and C-based Python tools like Cython + spaCy to develop some really fast natural language processing algorithms for text data. We’ll be able to tokenize, tag, normalize, vectorize, and dependency parse articles of text to derive valuable insights. No installation necessary, we'll do this together using Google Colab in the browser.		C Programming for Machine Learning - The ability to write implementations of machine learning algorithms in pure C allows developers to very efficiently manage memory allocation, concurrency, and control flow. That means fast implementations that can outperform preexisting models in other languages, including even (gasp) Python. It’s a useful skill to know and in this live stream I’ll use C and C-based Python tools like Cython + spaCy to develop some really fast natural language processing algorithms for text data. We’ll be able to tokenize, tag, normalize, vectorize, and dependency parse articles of text to derive valuable insights. No installation necessary, we'll do this together using Google Colab in the browser.
		+
		+	* [[spaCy]]

	<youtube>giF8XoPTMFg</youtube>		<youtube>giF8XoPTMFg</youtube>

@@ Line 7: / Line 7: @@
 <youtube>mXuEoqK4bEc</youtube>
 <youtube>gMvkiQ-gOW8</youtube>
 C Programming for Machine Learning - The ability to write implementations of machine learning algorithms in pure C allows developers to very efficiently manage memory allocation, concurrency, and control flow. That means fast implementations that can outperform preexisting models in other languages, including even (gasp) Python. It’s a useful skill to know and in this live stream I’ll use C and C-based Python tools like Cython + spaCy to develop some really fast natural language processing algorithms for text data. We’ll be able to tokenize, tag, normalize, vectorize, and dependency parse articles of text to derive valuable insights. No installation necessary, we'll do this together using Google Colab in the browser.
 <youtube>giF8XoPTMFg</youtube>