He loea i ka Exploratory Data Analysis

E ʻike i ke ʻano noʻeau o ka ʻikepili ʻikepili

I loko o kahi honua kahi i lilo ai ka ʻikepili i ka aila hou, ʻo ka ʻike ʻana i ka nānā ʻana he mākaukau koʻikoʻi. ʻO ka hoʻomaʻamaʻa "Perform Exploratory Data Analysis" i hāʻawi ʻia e OpenClassrooms he akua no ka poʻe e ʻimi nei e haku i kēia ʻano hana. Me ka lōʻihi o 15 mau hola, e ʻae kēia papa haʻahaʻa waena iā ʻoe e hoʻomaopopo i nā ʻano o kāu ʻikepili me nā ala ikaika e like me Principal Component Analysis (PCA) a me k-means clustering.

I loko o kēia hoʻomaʻamaʻa ʻana, e aʻo ʻoe pehea e hoʻokō ai i ka loiloi multidimensional exploratory, kahi mea hana pono no kēlā me kēia Data Analyst maikaʻi. E alakaʻi ʻia ʻoe i ka hoʻohana ʻana i nā ala kaulana e kālele wikiwiki i kāu hāpana, e hōʻemi ana i ka nui o ka helu o nā kānaka a i ʻole nā ​​​​mea hoʻololi. ʻO nā ʻano hiʻohiʻona e like me PCA e ʻae iā ʻoe e ʻike koke i nā ʻano nui i kāu laʻana, ma ka hōʻemi ʻana i ka helu o nā ʻano like ʻole e pono ai e hōʻike i kāu ʻikepili, ʻoiai e nalowale ana ka ʻike liʻiliʻi.

ʻO nā mea e pono ai no kēia papa he mākaukau o ka makemakika ma Terminale ES a i ʻole ka pae S, kahi ʻike maikaʻi o nā helu wehewehe wehewehe ʻelua a ʻelua, a me ka mākaukau o ka ʻōlelo Python a i ʻole R i loko o ka pōʻaiapili o ka ʻIke ʻIke. Pono ke kauoha maikaʻi o nā hale waihona puke pandas, NumPy a me Matplotlib inā koho ʻoe iā Python e like me kāu ʻōlelo papahana.

Luʻu i loko o kahi hoʻomaʻamaʻa waiwai a i kūkulu ʻia

ʻO ka hoʻomaka ʻana i ka ʻikepili ʻimi noiʻi pono e hoʻomaʻamaʻa ʻia a hoʻonohonoho pono ʻia. Hāʻawi ʻo OpenClassrooms iā ʻoe i kahi ala hoʻonaʻauao noʻonoʻo maikaʻi e alakaʻi iā ʻoe i nā pae like ʻole o ke aʻo ʻana. E hoʻomaka ʻoe me ka hoʻomaka ʻana i ka loiloi multidimensional exploratory, kahi e ʻike ai ʻoe i ka hoihoi o kēia ala a hui pū me nā poʻe loea i ke kula, e like me Emeric Nicolas, kahi ʻepekema data kaulana.

Ke holomua nei ʻoe ma ke aʻo ʻana, e hoʻolauna ʻia ʻoe i nā manaʻo kiʻekiʻe. ʻO ka ʻāpana ʻelua o ka papa e hoʻokomo iā ʻoe i ka honua o Principal Component Analysis (PCA), kahi ʻenehana e hiki ai iā ʻoe ke hoʻomaopopo i nā pilikia a me nā ʻano o ka hōʻemi ʻana. E aʻo nō hoʻi ʻoe i ka wehewehe ʻana i ka pōʻai o ka hoʻoponopono ʻana a koho i ka helu o nā ʻāpana e hoʻohana ai i kāu mau loiloi.

Akā ʻaʻole ʻo ia wale nō, ʻo ka hapakolu o ka papa e hoʻolauna iā ʻoe i nā ʻenehana hoʻokaʻawale ʻikepili. E aʻo ʻoe e pili ana i ka algorithm k-means, kahi ala kaulana no ka hoʻokaʻawale ʻana i kāu ʻikepili i nā hui like ʻole, a me nā ʻenehana clustering hierarchical. Pono kēia mau mākau no kēlā me kēia ʻikepili ʻikepili e ʻimi ana e unuhi i nā ʻike waiwai mai ka nui o ka ʻikepili.

He laulā kēia aʻo ʻana a hāʻawi iā ʻoe i nā mea hana e pono ai ʻoe e lilo i loea i ka ʻikepili ʻikepili. Hiki iā ʻoe ke hoʻokō i nā kānana ʻikepili ʻimi kūʻokoʻa a me ka maikaʻi, kahi akamai i ʻimi nui ʻia i ka honua ʻoihana i kēia mau lā.

E hoʻonui i kāu Horizons ʻOihana me ka hoʻomaʻamaʻa Pragmatic

Ma ke kahua ikaika o ka ʻepekema data, he mea koʻikoʻi ka loaʻa ʻana o nā mākau hana. Hoʻomākaukau kēia hoʻomaʻamaʻa iā ʻoe e hālāwai me nā pilikia maoli āu e hālāwai ai i kāu ʻoihana e hiki mai ana. Ma ka hoʻokomo ʻana iā ʻoe iho i nā haʻawina hihia maoli a me nā papahana hana, e loaʻa iā ʻoe ka manawa e hoʻomaʻamaʻa i ka ʻike theoretical i loaʻa.

ʻO kekahi o nā pōmaikaʻi nui o kēia aʻo ʻana, ʻo ia ke komo ʻana i kahi kaiāulu o nā haumāna like ʻole a me nā ʻoihana. Hiki iā ʻoe ke hoʻololi i nā manaʻo, kūkākūkā i nā manaʻo a me ka hui pū ʻana i nā papahana, e hana ana i kahi pūnaewele waiwai no kāu ʻoihana e hiki mai ana. Eia kekahi, hāʻawi ka OpenClassrooms platform iā ʻoe i ka nānā ponoʻī ʻana, e ʻae iā ʻoe e holomua ma kāu wikiwiki ʻoiai e pōmaikaʻi ana i ke kōkua ʻana o ka poʻe akamai i ke kula.

Eia kekahi, hāʻawi kēia hoʻomaʻamaʻa iā ʻoe i ka maʻalahi like ʻole, e ʻae iā ʻoe e hahai i nā papa ma kāu wikiwiki, mai ka ʻoluʻolu o kou home. ʻAʻole pono wale kēia ala hoʻonaʻauao hoʻonaʻauao, akā hoʻoikaika pū i ka hoʻomohala ʻana i ka hoʻopaʻa ʻana a me nā mākau hoʻokele manawa, nā waiwai waiwai i kēia ao ʻoihana.

I ka pōkole, ʻo kēia aʻo ʻana he ʻīpuka i kahi ʻoihana kūleʻa ma ke kahua o ka ʻepekema data. ʻAʻole wale ia e hoʻolako iā ʻoe me nā mākau theoretical paʻa, akā ʻo ka ʻike hana hoʻi e hoʻokaʻawale iā ʻoe i ka mākeke hana.